tensorflow_kaggle_dnn.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from __future__ import absolute_import\n",
    "from __future__ import division\n",
    "from __future__ import print_function\n",
    "\n",
    "import itertools\n",
    "import csv\n",
    "import pandas as pd\n",
    "import tensorflow as tf\n",
    "import random\n",
    "\n",
    "tf.logging.set_verbosity(tf.logging.INFO)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Continuous columns 50\n",
      "Categorical columns 29\n",
      "Total useful columns 80\n"
     ]
    }
   ],
   "source": [
    "#Divide columns\n",
    "CONTINUOUS_COLUMNS = [\"LotFrontage\",\"LotArea\",\"OverallQual\",\"OverallCond\",\"YearBuilt\",\"YearRemodAdd\",\"MasVnrArea\",\"ExterQual\",\"ExterCond\",\n",
    "\t\"BsmtQual\",\"BsmtCond\",\"BsmtExposure\",\"BsmtFinType1\",\"BsmtFinSF1\",\"BsmtFinType2\",\"BsmtFinSF2\",\"BsmtUnfSF\",\"TotalBsmtSF\",\"HeatingQC\",\n",
    "\t\"1stFlrSF\",\"2ndFlrSF\",\"LowQualFinSF\",\"GrLivArea\",\"BsmtFullBath\",\"BsmtHalfBath\",\"FullBath\",\"HalfBath\",\"BedroomAbvGr\",\"KitchenAbvGr\",\n",
    "\t\"KitchenQual\",\"TotRmsAbvGrd\",\"Functional\",\"Fireplaces\",\"FireplaceQu\",\"GarageYrBlt\",\"GarageFinish\",\"GarageCars\",\n",
    "\t\"GarageArea\",\"GarageQual\",\"GarageCond\",\"WoodDeckSF\",\"OpenPorchSF\",\"EnclosedPorch\",\"3SsnPorch\",\"ScreenPorch\",\"PoolArea\",\"PoolQC\",\n",
    "\t\"MiscVal\",\"MoSold\",\"YrSold\"]\n",
    "CATEGORICAL_COLUMNS = [\"MSSubClass\",\"MSZoning\",\"Street\",\"Alley\",\"LotShape\",\"LandContour\",\"Utilities\",\"LotConfig\",\"LandSlope\",\"Neighborhood\",\n",
    "\t\"Condition1\",\"Condition2\",\"BldgType\",\"HouseStyle\",\"RoofStyle\",\"RoofMatl\",\"Exterior1st\",\"Exterior2nd\",\"MasVnrType\",\n",
    "\t\"Foundation\",\"Heating\",\"CentralAir\",\"Electrical\",\"GarageType\",\"PavedDrive\",\"Fence\",\"MiscFeature\",\"SaleType\",\"SaleCondition\"]\n",
    "LABEL_COLUMN = \"SalePrice\"\n",
    "COLUMNS = CONTINUOUS_COLUMNS + CATEGORICAL_COLUMNS + [LABEL_COLUMN]\n",
    "print(\"Continuous columns {0:2d}\".format(len(CONTINUOUS_COLUMNS)))\n",
    "print(\"Categorical columns {0:2d}\".format(len(CATEGORICAL_COLUMNS)))\n",
    "print(\"Total useful columns {0:2d}\".format(len(COLUMNS)))\n",
    "\n",
    "#global variables\n",
    "max_price = 755000.0\n",
    "min_price = 34900.0\n",
    "scale = 1.0\n",
    "price_offset = min_price\n",
    "price_range = (max_price-min_price)/scale\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def input_clean(raw_data):\n",
    "    data = raw_data.drop('Id', 1).copy()\n",
    "    data = data.replace({                            \n",
    "                            'MSSubClass':{\n",
    "                                            20:'class20',\n",
    "                                            30:'class30',\n",
    "                                            40:'class40',\n",
    "                                            45:'class45',\n",
    "                                            50:'class50',\n",
    "                                            60:'class60',\n",
    "                                            70:'class70',\n",
    "                                            75:'class75',\n",
    "                                            80:'class80',\n",
    "                                            85:'class85',\n",
    "                                            90:'class90',\n",
    "                                            120:'class120',\n",
    "                                            150:'class150',\n",
    "                                            160:'class160',\n",
    "                                            180:'class180',\n",
    "                                            190:'class190'\n",
    "                                            },\n",
    "                            'MSZoning': {'C (all)': 'C'\n",
    "                                            },\n",
    "                            'ExterQual': {'Ex': 5, \n",
    "                                            'Gd': 4, \n",
    "                                            'TA': 3, \n",
    "                                            'Fa': 2,\n",
    "                                            'Po': 1\n",
    "                                            },\n",
    "                            'ExterCond': {'Ex': 5, \n",
    "                                            'Gd': 4, \n",
    "                                            'TA': 3, \n",
    "                                            'Fa': 2,\n",
    "                                            'Po': 1\n",
    "                                            },\n",
    "                            'BsmtQual':{ \n",
    "                                            'Ex':5,\n",
    "                                            'Gd':4,\n",
    "                                            'TA':3,\n",
    "                                            'Fa':2,\n",
    "                                            'Po':1,\n",
    "                                            'NoBsmt': 0},\n",
    "                            'BsmtCond': {'Ex': 5, \n",
    "                                            'Gd': 4, \n",
    "                                            'TA': 3, \n",
    "                                            'Fa': 2,\n",
    "                                            'Po': 1,\n",
    "                                            'NoBsmt': 0},\n",
    "                            'BsmtExposure': {'Gd':4,\n",
    "                                            'Av':3,\n",
    "                                            'Mn':2,\n",
    "                                            'No':1,\n",
    "                                            'NoBsmt':0},\n",
    "                            'BsmtFinType1':{'GLQ':6,\n",
    "                                            'ALQ':5,\n",
    "                                            'BLQ':4,\n",
    "                                            'Rec':3,\n",
    "                                            'LwQ':2,\n",
    "                                            'Unf':1,\n",
    "                                            'NoBsmt':0},\n",
    "                            'BsmtFinType2':{\n",
    "                                            'GLQ':6,\n",
    "                                            'ALQ':5,\n",
    "                                            'BLQ':4,\n",
    "                                            'Rec':3,\n",
    "                                            'LwQ':2,\n",
    "                                            'Unf':1,\n",
    "                                            'NoBsmt':0},\n",
    "                            'HeatingQC': {'Ex': 5, \n",
    "                                            'Gd': 4, \n",
    "                                            'TA': 3, \n",
    "                                            'Fa': 2,\n",
    "                                            'Po': 1\n",
    "                                            },\n",
    "                            'KitchenQual': {'Ex': 5, \n",
    "                                            'Gd': 4, \n",
    "                                            'TA': 3, \n",
    "                                            'Fa': 2,\n",
    "                                            'Po': 1,\n",
    "                                            'NoKit':0},\n",
    "                            'Functional': {'Typ': 8,\n",
    "                                            'Min1': 7,\n",
    "                                            'Min2': 6,\n",
    "                                            'Mod': 5,\n",
    "                                            'Maj1': 4,\n",
    "                                            'Maj2': 3,\n",
    "                                            'Sev': 2,\n",
    "                                            'Sal': 1,\n",
    "                                            'NoFunc':0},\n",
    "                            'FireplaceQu': {'Ex': 5, \n",
    "                                            'Gd': 4, \n",
    "                                            'TA': 3, \n",
    "                                            'Fa': 2,\n",
    "                                            'Po': 1,\n",
    "                                            'NoFireplace': 0 \n",
    "                                            },\n",
    "                            'GarageFinish': {\n",
    "                                            'Fin':3,\n",
    "                                            'RFn':2,\n",
    "                                            'Unf':1,\n",
    "                                            'NoGarage':0\n",
    "                                             },\n",
    "                            'GarageQual': {'Ex': 5, \n",
    "                                            'Gd': 4, \n",
    "                                            'TA': 3, \n",
    "                                            'Fa': 2,\n",
    "                                            'Po': 1,\n",
    "                                            'NoGarage': 0},\n",
    "                            'GarageCond': {'Ex': 5, \n",
    "                                            'Gd': 4, \n",
    "                                            'TA': 3, \n",
    "                                            'Fa': 2,\n",
    "                                            'Po': 1,\n",
    "                                            'NoGarage': 0},\n",
    "                            'PoolQC': {'Ex':4,\n",
    "                                            'Gd':3,\n",
    "                                            'TA':2,\n",
    "                                            'Fa':1,\n",
    "                                            'NoPool':0\n",
    "                                       }\n",
    "                            })\n",
    "    #fill NaN\n",
    "    #CONTINUOUS_COLUMNS\n",
    "    data['LotFrontage']=data['LotFrontage'].fillna(0)\n",
    "    data['MasVnrArea']=data['MasVnrArea'].fillna(0)\n",
    "    data['GarageYrBlt']=data['GarageYrBlt'].fillna(1899)\n",
    "    data['BsmtFinSF1']=data['BsmtFinSF1'].fillna(0)\n",
    "    data['BsmtFinSF2']=data['BsmtFinSF2'].fillna(0)\n",
    "    data['BsmtUnfSF']=data['BsmtUnfSF'].fillna(0)\n",
    "    data['TotalBsmtSF']=data['TotalBsmtSF'].fillna(0)\n",
    "    data['BsmtFullBath']=data['BsmtFullBath'].fillna(0)\n",
    "    data['BsmtHalfBath']=data['BsmtHalfBath'].fillna(0)\n",
    "    data['GarageCars']=data['GarageCars'].fillna(0)\n",
    "    data['GarageArea']=data['GarageArea'].fillna(0)\n",
    "\n",
    "    #CONTINUOUS_COLUMNS==>CATEGORICAL_COLUMNS\n",
    "    data['BsmtQual']=data['BsmtQual'].fillna(0)\n",
    "    data['BsmtCond']=data['BsmtCond'].fillna(0)\n",
    "    data['BsmtExposure']=data['BsmtExposure'].fillna(0)\n",
    "    data['BsmtFinType1']=data['BsmtFinType1'].fillna(0)\n",
    "    data['BsmtFinType2']=data['BsmtFinType1'].fillna(0)\n",
    "    data['FireplaceQu']=data['FireplaceQu'].fillna(0)\n",
    "    data['GarageFinish']=data['GarageFinish'].fillna(0)\n",
    "    data['GarageQual']=data['GarageQual'].fillna(0)\n",
    "    data['GarageCond']=data['GarageCond'].fillna(0)\n",
    "    data['PoolQC']=data['PoolQC'].fillna(0)\n",
    "    data['KitchenQual']=data['KitchenQual'].fillna(0)\n",
    "    data['Functional']=data['Functional'].fillna(0)\n",
    "    \n",
    "    #CATEGORICAL_COLUMNS\n",
    "    data['MSZoning'] = data['MSZoning'].fillna('None')\n",
    "    data['Utilities'] = data['Utilities'].fillna('None')\n",
    "    data['Exterior1st'] = data['Exterior1st'].fillna('None')\n",
    "    data['Exterior2nd'] = data['Exterior2nd'].fillna('None')\n",
    "    data['SaleType'] = data['SaleType'].fillna('None')\n",
    "    data['Alley']=data['Alley'].fillna('NoAlley')\n",
    "    data['MasVnrType']=data['MasVnrType'].fillna('NoMasVnr')\n",
    "    data['GarageType']=data['GarageType'].fillna('NoGarage')\n",
    "    data['Electrical']=data['Electrical'].fillna('NoElec')\n",
    "    data['Fence']=data['Fence'].fillna('NoFc')\n",
    "    data['MiscFeature']=data['MiscFeature'].fillna('NoFtr')\n",
    "    \n",
    "    return data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'Id': 1}\n"
     ]
    }
   ],
   "source": [
    "#Check if the COLUMNS is match with the original data\n",
    "folder = '/Users/lanxing/Desktop/Machine Learning/kaggle/'\n",
    "check_columns = pd.read_csv(folder+\"train.csv\").columns.tolist()\n",
    "check_dict = {}\n",
    "for l in check_columns:\n",
    "    check_dict[l] = 1\n",
    "for l in COLUMNS:\n",
    "    if l in check_dict:\n",
    "        del check_dict[l]\n",
    "    else:\n",
    "        check_dict[l] = -1\n",
    "print(check_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "folder = '/Users/lanxing/Desktop/Machine Learning/kaggle/'\n",
    "raw_train = pd.read_csv(folder+\"train.csv\")\n",
    "#print(raw_train.shape)\n",
    "#i=0\n",
    "#while i<raw_train.describe().shape[1]:\n",
    "#    print(raw_train.describe().iloc[:,i:min(i+9,raw_train.describe().shape[1])])\n",
    "#    i=i+10\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "#Describe the training data after cleaning\n",
    "train = input_clean(raw_train)\n",
    "#print(train.describe().shape[1])\n",
    "#print(train.iloc[36:45,21:40])\n",
    "#i=0\n",
    "#while i<train.describe().shape[1]:\n",
    "#    print(train.describe().iloc[:,i:min(i+9,train.describe().shape[1])])\n",
    "#    i=i+10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'SalePrice': 1}\n"
     ]
    }
   ],
   "source": [
    "#Check the cleaning data\n",
    "check_columns = train.describe().columns.tolist()\n",
    "check_dict = {}\n",
    "for l in check_columns:\n",
    "    check_dict[l] = 1\n",
    "for l in CONTINUOUS_COLUMNS:\n",
    "    if l in check_dict:\n",
    "        del check_dict[l]\n",
    "    else:\n",
    "        check_dict[l] = -1\n",
    "print(check_dict)\n",
    "for l in train.columns.tolist():\n",
    "    if train.loc[:,l].isnull().values.any():\n",
    "        print(l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "#If input_stat.csv file does not exist, uncomment this part to calculate statistical data\n",
    "\n",
    "input_stat = train.describe().loc[['min','max'],:]\n",
    "#max_price = input_stat.loc['max','SalePrice'].tolist()\n",
    "#min_price = input_stat.loc['min','SalePrice'].tolist()\n",
    "input_stat.to_csv(folder+\"input_stat.csv\")\n",
    "#print(type(max_price),type(min_price))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#Define function to normalize data\n",
    "def input_normalize(data,istrain):\n",
    "    input_stat = pd.DataFrame.from_csv(folder+\"input_stat.csv\",index_col = 0)\n",
    "    data_normal = data.copy()\n",
    "    columns = input_stat.columns\n",
    "    if (istrain == False):\n",
    "        columns = columns.drop(u'SalePrice')\n",
    "    for k in columns:\n",
    "        col_offset = input_stat.loc['min',k]\n",
    "        col_range = (input_stat.loc['max',k]-input_stat.loc['min',k])/scale\n",
    "        #print(k,col_min,col_range)\n",
    "        data_normal[k] = (data_normal[k]-col_offset)/col_range\n",
    "    max_price = input_stat.loc['max','SalePrice']*scale\n",
    "    min_price = input_stat.loc['min','SalePrice']*scale\n",
    "    price_offset = min_price/2\n",
    "    price_range = (max_price-min_price)/scale\n",
    "    return data_normal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#Normalize data\n",
    "train_normal = input_normalize(train,True)\n",
    "#print(train_normal.iloc[0:20,0:20])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def input_pdtotf(df,istrain):\n",
    "    # Creates a dictionary mapping from each continuous feature column name (k) to\n",
    "    # the values of that column stored in a constant Tensor.\n",
    "    continuous_cols = {k: tf.constant(df[k].values)\n",
    "                     for k in CONTINUOUS_COLUMNS}\n",
    "    # Creates a dictionary mapping from each categorical feature column name (k)\n",
    "    # to the values of that column stored in a tf.SparseTensor.\n",
    "    categorical_cols = {k: tf.SparseTensor(\n",
    "        indices=[[i, 0] for i in range(df[k].size)],\n",
    "        values=df[k].values,\n",
    "        shape=[df[k].size, 1])\n",
    "                      for k in CATEGORICAL_COLUMNS}\n",
    "    # Merges the two dictionaries into one.\n",
    "    feature_cols = dict(continuous_cols.items() + categorical_cols.items())\n",
    "    #feature_cols = dict(continuous_cols.items())\n",
    "    # Converts the label column into a constant Tensor.\n",
    "    if(istrain == True):\n",
    "        label = tf.constant(df[LABEL_COLUMN].values)\n",
    "        # Returns the feature columns and the label.\n",
    "        return feature_cols, label\n",
    "    else:\n",
    "        return feature_cols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "#categorical_options = {}\n",
    "#for l in CATEGORICAL_COLUMNS:\n",
    "#    categorical_options[l]=train.loc[:,l].value_counts().index.values.tolist()\n",
    "#print(categorical_options)\n",
    "CATEGORICAL_OPTIONS = {'MasVnrType': ['None', 'BrkFace', 'Stone', 'BrkCmn', 'NoMasVnr'], \n",
    "                       'LotConfig': ['Inside', 'Corner', 'CulDSac', 'FR2', 'FR3'], \n",
    "                       'Exterior1st': ['VinylSd', 'HdBoard', 'MetalSd', 'Wd Sdng', 'Plywood', 'CemntBd', 'BrkFace', 'WdShing', 'Stucco', 'AsbShng', 'Stone', 'BrkComm', 'AsphShn', 'ImStucc', 'CBlock','None'], \n",
    "                       'Electrical': ['SBrkr', 'FuseA', 'FuseF', 'FuseP', 'Mix', 'NoElec'], \n",
    "                       'HouseStyle': ['1Story', '2Story', '1.5Fin', 'SLvl', 'SFoyer', '1.5Unf', '2.5Unf', '2.5Fin'], \n",
    "                       'Foundation': ['PConc', 'CBlock', 'BrkTil', 'Slab', 'Stone', 'Wood'], \n",
    "                       'GarageType': ['Attchd', 'Detchd', 'BuiltIn', 'NoGarage', 'Basment', 'CarPort', '2Types'], \n",
    "                       'RoofStyle': ['Gable', 'Hip', 'Flat', 'Gambrel', 'Mansard', 'Shed'], \n",
    "                       'CentralAir': ['Y', 'N'], \n",
    "                       'Utilities': ['AllPub', 'NoSeWa','None'], \n",
    "                       'LotShape': ['Reg', 'IR1', 'IR2', 'IR3'], \n",
    "                       'MiscFeature': ['NoFtr', 'Shed', 'Othr', 'Gar2', 'TenC'], \n",
    "                       'PavedDrive': ['Y', 'N', 'P'], \n",
    "                       'LandSlope': ['Gtl', 'Mod', 'Sev'], \n",
    "                       'SaleType': ['WD', 'New', 'COD', 'ConLD', 'ConLw', 'ConLI', 'CWD', 'Oth', 'Con','None'], \n",
    "                       'Heating': ['GasA', 'GasW', 'Grav', 'Wall', 'OthW', 'Floor'], \n",
    "                       'Exterior2nd': ['VinylSd', 'MetalSd', 'HdBoard', 'Wd Sdng', 'Plywood', 'CmentBd', 'Wd Shng', 'Stucco', 'BrkFace', 'AsbShng', 'ImStucc', 'Brk Cmn', 'Stone', 'AsphShn', 'Other', 'CBlock','None'], \n",
    "                       'MSSubClass': ['class20', 'class60', 'class50', 'class120', 'class30', 'class160', 'class70', 'class80', 'class90', 'class190', 'class85', 'class75', 'class45', 'class180', 'class40'], \n",
    "                       'Condition2': ['Norm', 'Feedr', 'Artery', 'RRNn', 'PosN', 'RRAn', 'RRAe', 'PosA'], \n",
    "                       'Condition1': ['Norm', 'Feedr', 'Artery', 'RRAn', 'PosN', 'RRAe', 'PosA', 'RRNn', 'RRNe'], \n",
    "                       'LandContour': ['Lvl', 'Bnk', 'HLS', 'Low'], \n",
    "                       'RoofMatl': ['CompShg', 'Tar&Grv', 'WdShngl', 'WdShake', 'Membran', 'Metal', 'ClyTile', 'Roll'], \n",
    "                       'Neighborhood': ['NAmes', 'CollgCr', 'OldTown', 'Edwards', 'Somerst', 'Gilbert', 'NridgHt', 'Sawyer', 'NWAmes', 'SawyerW', 'BrkSide', 'Crawfor', 'Mitchel', 'NoRidge', 'Timber', 'IDOTRR', 'ClearCr', 'SWISU', 'StoneBr', 'MeadowV', 'Blmngtn', 'BrDale', 'Veenker', 'NPkVill', 'Blueste'], \n",
    "                       'Fence': ['NoFc', 'MnPrv', 'GdPrv', 'GdWo', 'MnWw'], \n",
    "                       'SaleCondition': ['Normal', 'Partial', 'Abnorml', 'Family', 'Alloca', 'AdjLand'], \n",
    "                       'BldgType': ['1Fam', 'TwnhsE', 'Duplex', 'Twnhs', '2fmCon'], \n",
    "                       'Alley': ['NoAlley', 'Grvl', 'Pave'], \n",
    "                       'Street': ['Pave', 'Grvl'], \n",
    "                       'MSZoning': ['RL', 'RM', 'FV', 'RH', 'C','None']}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:The default value of combiner will change from \"sum\" to \"sqrtn\" after 2016/11/01.\n",
      "WARNING:tensorflow:The default value of combiner will change from \"sum\" to \"sqrtn\" after 2016/11/01.\n",
      "WARNING:tensorflow:The default value of combiner will change from \"sum\" to \"sqrtn\" after 2016/11/01.\n",
      "WARNING:tensorflow:The default value of combiner will change from \"sum\" to \"sqrtn\" after 2016/11/01.\n",
      "WARNING:tensorflow:The default value of combiner will change from \"sum\" to \"sqrtn\" after 2016/11/01.\n",
      "WARNING:tensorflow:The default value of combiner will change from \"sum\" to \"sqrtn\" after 2016/11/01.\n",
      "WARNING:tensorflow:The default value of combiner will change from \"sum\" to \"sqrtn\" after 2016/11/01.\n",
      "WARNING:tensorflow:The default value of combiner will change from \"sum\" to \"sqrtn\" after 2016/11/01.\n",
      "WARNING:tensorflow:The default value of combiner will change from \"sum\" to \"sqrtn\" after 2016/11/01.\n",
      "WARNING:tensorflow:The default value of combiner will change from \"sum\" to \"sqrtn\" after 2016/11/01.\n",
      "WARNING:tensorflow:The default value of combiner will change from \"sum\" to \"sqrtn\" after 2016/11/01.\n",
      "WARNING:tensorflow:The default value of combiner will change from \"sum\" to \"sqrtn\" after 2016/11/01.\n",
      "WARNING:tensorflow:The default value of combiner will change from \"sum\" to \"sqrtn\" after 2016/11/01.\n",
      "WARNING:tensorflow:The default value of combiner will change from \"sum\" to \"sqrtn\" after 2016/11/01.\n",
      "WARNING:tensorflow:The default value of combiner will change from \"sum\" to \"sqrtn\" after 2016/11/01.\n",
      "WARNING:tensorflow:The default value of combiner will change from \"sum\" to \"sqrtn\" after 2016/11/01.\n",
      "WARNING:tensorflow:The default value of combiner will change from \"sum\" to \"sqrtn\" after 2016/11/01.\n",
      "WARNING:tensorflow:The default value of combiner will change from \"sum\" to \"sqrtn\" after 2016/11/01.\n",
      "WARNING:tensorflow:The default value of combiner will change from \"sum\" to \"sqrtn\" after 2016/11/01.\n",
      "WARNING:tensorflow:The default value of combiner will change from \"sum\" to \"sqrtn\" after 2016/11/01.\n",
      "WARNING:tensorflow:The default value of combiner will change from \"sum\" to \"sqrtn\" after 2016/11/01.\n",
      "WARNING:tensorflow:The default value of combiner will change from \"sum\" to \"sqrtn\" after 2016/11/01.\n",
      "WARNING:tensorflow:The default value of combiner will change from \"sum\" to \"sqrtn\" after 2016/11/01.\n",
      "WARNING:tensorflow:The default value of combiner will change from \"sum\" to \"sqrtn\" after 2016/11/01.\n",
      "WARNING:tensorflow:The default value of combiner will change from \"sum\" to \"sqrtn\" after 2016/11/01.\n",
      "WARNING:tensorflow:The default value of combiner will change from \"sum\" to \"sqrtn\" after 2016/11/01.\n",
      "WARNING:tensorflow:The default value of combiner will change from \"sum\" to \"sqrtn\" after 2016/11/01.\n",
      "WARNING:tensorflow:The default value of combiner will change from \"sum\" to \"sqrtn\" after 2016/11/01.\n",
      "WARNING:tensorflow:The default value of combiner will change from \"sum\" to \"sqrtn\" after 2016/11/01.\n",
      "WARNING:tensorflow:Using temporary folder as model directory: /var/folders/5x/z33hrhcn4tqfk2tk0d1ffp4w0000gn/T/tmpW1MmPy\n",
      "INFO:tensorflow:Using default config.\n",
      "INFO:tensorflow:Using config: {'save_summary_steps': 100, '_num_ps_replicas': 0, '_task_type': None, '_environment': 'local', '_is_chief': True, 'save_checkpoints_secs': 600, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x1231b1d90>, 'tf_config': gpu_options {\n",
      "  per_process_gpu_memory_fraction: 1\n",
      "}\n",
      ", '_task_id': 0, 'tf_random_seed': None, 'keep_checkpoint_every_n_hours': 10000, '_evaluation_master': '', 'save_checkpoints_steps': None, '_master': '', 'keep_checkpoint_max': 5}\n"
     ]
    }
   ],
   "source": [
    "#Defining FeatureColumns and Creating the Regressor\n",
    "# Creates features column from each continuous feature column name (k) to\n",
    "continuous_feature = [tf.contrib.layers.real_valued_column(k)\n",
    "                  for k in CONTINUOUS_COLUMNS]\n",
    "# Creates features column from each categorical feature column name (k)\n",
    "#categorical_feature = [tf.contrib.layers.embedding_column(tf.contrib.layers.sparse_column_with_keys(\n",
    "#                      column_name=k, keys=CATEGORICAL_OPTIONS[k]),dimension=8) for k in CATEGORICAL_COLUMNS]\n",
    "categorical_feature = [tf.contrib.layers.one_hot_column(tf.contrib.layers.sparse_column_with_keys(\n",
    "                      column_name=k, keys=CATEGORICAL_OPTIONS[k])) for k in CATEGORICAL_COLUMNS]\n",
    "#categorical_feature = [tf.contrib.layers.embedding_column(tf.contrib.layers.sparse_column_with_hash_bucket(k, hash_bucket_size=30),dimension=30) for k in CATEGORICAL_COLUMNS]\n",
    "\n",
    "\n",
    "feature_cols = continuous_feature + categorical_feature\n",
    "regressor = tf.contrib.learn.DNNRegressor(\n",
    "    feature_columns=feature_cols, hidden_units=[100, 100, 100, 100])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "INFO:tensorflow:Summary name dnn/hiddenlayer_0:fraction_of_zero_values is illegal; using dnn/hiddenlayer_0_fraction_of_zero_values instead.\n",
      "INFO:tensorflow:Summary name dnn/hiddenlayer_0:activation is illegal; using dnn/hiddenlayer_0_activation instead.\n",
      "INFO:tensorflow:Summary name dnn/hiddenlayer_1:fraction_of_zero_values is illegal; using dnn/hiddenlayer_1_fraction_of_zero_values instead.\n",
      "INFO:tensorflow:Summary name dnn/hiddenlayer_1:activation is illegal; using dnn/hiddenlayer_1_activation instead.\n",
      "INFO:tensorflow:Summary name dnn/hiddenlayer_2:fraction_of_zero_values is illegal; using dnn/hiddenlayer_2_fraction_of_zero_values instead.\n",
      "INFO:tensorflow:Summary name dnn/hiddenlayer_2:activation is illegal; using dnn/hiddenlayer_2_activation instead.\n",
      "INFO:tensorflow:Summary name dnn/hiddenlayer_3:fraction_of_zero_values is illegal; using dnn/hiddenlayer_3_fraction_of_zero_values instead.\n",
      "INFO:tensorflow:Summary name dnn/hiddenlayer_3:activation is illegal; using dnn/hiddenlayer_3_activation instead.\n",
      "INFO:tensorflow:Summary name logits:fraction_of_zero_values is illegal; using logits_fraction_of_zero_values instead.\n",
      "INFO:tensorflow:Summary name logits:activation is illegal; using logits_activation instead.\n",
      "INFO:tensorflow:Create CheckpointSaverHook.\n",
      "INFO:tensorflow:loss = 0.0188106, step = 1\n",
      "INFO:tensorflow:Saving checkpoints for 1 into /var/folders/5x/z33hrhcn4tqfk2tk0d1ffp4w0000gn/T/tmpW1MmPy/model.ckpt.\n",
      "WARNING:tensorflow:*******************************************************\n",
      "WARNING:tensorflow:TensorFlow's V1 checkpoint format has been deprecated.\n",
      "WARNING:tensorflow:Consider switching to the more efficient V2 format:\n",
      "WARNING:tensorflow:   `tf.train.Saver(write_version=tf.train.SaverDef.V2)`\n",
      "WARNING:tensorflow:now on by default.\n",
      "WARNING:tensorflow:*******************************************************\n",
      "INFO:tensorflow:loss = 0.00399673, step = 101\n",
      "INFO:tensorflow:global_step/sec: 21.2365\n",
      "INFO:tensorflow:loss = 0.00395262, step = 201\n",
      "INFO:tensorflow:global_step/sec: 46.9889\n",
      "INFO:tensorflow:loss = 0.00286494, step = 301\n",
      "INFO:tensorflow:global_step/sec: 42.591\n",
      "INFO:tensorflow:loss = 0.0025585, step = 401\n",
      "INFO:tensorflow:global_step/sec: 47.4168\n",
      "INFO:tensorflow:loss = 0.00229083, step = 501\n",
      "INFO:tensorflow:global_step/sec: 47.908\n",
      "INFO:tensorflow:loss = 0.00207682, step = 601\n",
      "INFO:tensorflow:global_step/sec: 46.1977\n",
      "INFO:tensorflow:loss = 0.00187732, step = 701\n",
      "INFO:tensorflow:global_step/sec: 42.7588\n",
      "INFO:tensorflow:loss = 0.00172074, step = 801\n",
      "INFO:tensorflow:global_step/sec: 43.2893\n",
      "INFO:tensorflow:loss = 0.00165094, step = 901\n",
      "INFO:tensorflow:global_step/sec: 39.8324\n",
      "INFO:tensorflow:loss = 0.00152026, step = 1001\n",
      "INFO:tensorflow:global_step/sec: 40.5682\n",
      "INFO:tensorflow:loss = 0.00140454, step = 1101\n",
      "INFO:tensorflow:global_step/sec: 47.7975\n",
      "INFO:tensorflow:loss = 0.00135147, step = 1201\n",
      "INFO:tensorflow:global_step/sec: 42.2849\n",
      "INFO:tensorflow:loss = 0.00127923, step = 1301\n",
      "INFO:tensorflow:global_step/sec: 43.5475\n",
      "INFO:tensorflow:loss = 0.00117729, step = 1401\n",
      "INFO:tensorflow:global_step/sec: 45.8007\n",
      "INFO:tensorflow:loss = 0.00112014, step = 1501\n",
      "INFO:tensorflow:global_step/sec: 48.0547\n",
      "INFO:tensorflow:loss = 0.00106739, step = 1601\n",
      "INFO:tensorflow:global_step/sec: 47.5658\n",
      "INFO:tensorflow:loss = 0.00103047, step = 1701\n",
      "INFO:tensorflow:global_step/sec: 44.314\n",
      "INFO:tensorflow:loss = 0.000978204, step = 1801\n",
      "INFO:tensorflow:global_step/sec: 46.0464\n",
      "INFO:tensorflow:loss = 0.000940253, step = 1901\n",
      "INFO:tensorflow:global_step/sec: 45.3445\n",
      "INFO:tensorflow:loss = 0.000907778, step = 2001\n",
      "INFO:tensorflow:global_step/sec: 45.2277\n",
      "INFO:tensorflow:loss = 0.000833274, step = 2101\n",
      "INFO:tensorflow:global_step/sec: 44.983\n",
      "INFO:tensorflow:loss = 0.00079105, step = 2201\n",
      "INFO:tensorflow:global_step/sec: 44.0927\n",
      "INFO:tensorflow:loss = 0.000764573, step = 2301\n",
      "INFO:tensorflow:global_step/sec: 45.1684\n",
      "INFO:tensorflow:loss = 0.00076694, step = 2401\n",
      "INFO:tensorflow:global_step/sec: 48.7417\n",
      "INFO:tensorflow:loss = 0.000756321, step = 2501\n",
      "INFO:tensorflow:global_step/sec: 49.0747\n",
      "INFO:tensorflow:loss = 0.000692716, step = 2601\n",
      "INFO:tensorflow:global_step/sec: 48.5556\n",
      "INFO:tensorflow:loss = 0.000681782, step = 2701\n",
      "INFO:tensorflow:global_step/sec: 43.6972\n",
      "INFO:tensorflow:loss = 0.000656932, step = 2801\n",
      "INFO:tensorflow:global_step/sec: 45.5745\n",
      "INFO:tensorflow:loss = 0.000620457, step = 2901\n",
      "INFO:tensorflow:global_step/sec: 47.7265\n",
      "INFO:tensorflow:loss = 0.000615691, step = 3001\n",
      "INFO:tensorflow:global_step/sec: 41.4335\n",
      "INFO:tensorflow:loss = 0.000600866, step = 3101\n",
      "INFO:tensorflow:global_step/sec: 43.9161\n",
      "INFO:tensorflow:loss = 0.000597226, step = 3201\n",
      "INFO:tensorflow:global_step/sec: 41.6231\n",
      "INFO:tensorflow:loss = 0.000596465, step = 3301\n",
      "INFO:tensorflow:global_step/sec: 36.129\n",
      "INFO:tensorflow:loss = 0.000565185, step = 3401\n",
      "INFO:tensorflow:global_step/sec: 44.9408\n",
      "INFO:tensorflow:loss = 0.000536909, step = 3501\n",
      "INFO:tensorflow:global_step/sec: 36.2235\n",
      "INFO:tensorflow:loss = 0.000498576, step = 3601\n",
      "INFO:tensorflow:global_step/sec: 38.3433\n",
      "INFO:tensorflow:loss = 0.00051812, step = 3701\n",
      "INFO:tensorflow:global_step/sec: 34.1138\n",
      "INFO:tensorflow:loss = 0.000516753, step = 3801\n",
      "INFO:tensorflow:global_step/sec: 43.7166\n",
      "INFO:tensorflow:loss = 0.000471715, step = 3901\n",
      "INFO:tensorflow:global_step/sec: 42.9018\n",
      "INFO:tensorflow:loss = 0.000474447, step = 4001\n",
      "INFO:tensorflow:global_step/sec: 36.2992\n",
      "INFO:tensorflow:loss = 0.000482232, step = 4101\n",
      "INFO:tensorflow:global_step/sec: 46.2131\n",
      "INFO:tensorflow:loss = 0.000439181, step = 4201\n",
      "INFO:tensorflow:global_step/sec: 49.2956\n",
      "INFO:tensorflow:loss = 0.000434555, step = 4301\n",
      "INFO:tensorflow:global_step/sec: 42.4133\n",
      "INFO:tensorflow:loss = 0.000422892, step = 4401\n",
      "INFO:tensorflow:global_step/sec: 33.5036\n",
      "INFO:tensorflow:loss = 0.000415336, step = 4501\n",
      "INFO:tensorflow:global_step/sec: 43.4082\n",
      "INFO:tensorflow:loss = 0.000427006, step = 4601\n",
      "INFO:tensorflow:global_step/sec: 42.5415\n",
      "INFO:tensorflow:loss = 0.000399705, step = 4701\n",
      "INFO:tensorflow:global_step/sec: 42.8077\n",
      "INFO:tensorflow:loss = 0.000373514, step = 4801\n",
      "INFO:tensorflow:global_step/sec: 35.8544\n",
      "INFO:tensorflow:loss = 0.000392575, step = 4901\n",
      "INFO:tensorflow:global_step/sec: 38.8823\n",
      "INFO:tensorflow:loss = 0.000400947, step = 5001\n",
      "INFO:tensorflow:global_step/sec: 40.1307\n",
      "INFO:tensorflow:loss = 0.000343118, step = 5101\n",
      "INFO:tensorflow:global_step/sec: 42.6688\n",
      "INFO:tensorflow:loss = 0.000402126, step = 5201\n",
      "INFO:tensorflow:global_step/sec: 44.8789\n",
      "INFO:tensorflow:loss = 0.000331028, step = 5301\n",
      "INFO:tensorflow:global_step/sec: 30.0273\n",
      "INFO:tensorflow:loss = 0.000370917, step = 5401\n",
      "INFO:tensorflow:global_step/sec: 37.7082\n",
      "INFO:tensorflow:loss = 0.000319226, step = 5501\n",
      "INFO:tensorflow:global_step/sec: 47.3468\n",
      "INFO:tensorflow:loss = 0.000342593, step = 5601\n",
      "INFO:tensorflow:global_step/sec: 40.9481\n",
      "INFO:tensorflow:loss = 0.000324709, step = 5701\n",
      "INFO:tensorflow:global_step/sec: 44.885\n",
      "INFO:tensorflow:loss = 0.000317526, step = 5801\n",
      "INFO:tensorflow:global_step/sec: 47.7374\n",
      "INFO:tensorflow:loss = 0.00033419, step = 5901\n",
      "INFO:tensorflow:global_step/sec: 45.8328\n",
      "INFO:tensorflow:loss = 0.000293848, step = 6001\n",
      "INFO:tensorflow:global_step/sec: 46.8077\n",
      "INFO:tensorflow:loss = 0.000345124, step = 6101\n",
      "INFO:tensorflow:global_step/sec: 35.5976\n",
      "INFO:tensorflow:loss = 0.000273557, step = 6201\n",
      "INFO:tensorflow:global_step/sec: 40.2374\n",
      "INFO:tensorflow:loss = 0.000334125, step = 6301\n",
      "INFO:tensorflow:global_step/sec: 48.1277\n",
      "INFO:tensorflow:loss = 0.000277483, step = 6401\n",
      "INFO:tensorflow:global_step/sec: 48.517\n",
      "INFO:tensorflow:loss = 0.000297291, step = 6501\n",
      "INFO:tensorflow:global_step/sec: 48.6396\n",
      "INFO:tensorflow:loss = 0.000271484, step = 6601\n",
      "INFO:tensorflow:global_step/sec: 42.1827\n",
      "INFO:tensorflow:loss = 0.000288649, step = 6701\n",
      "INFO:tensorflow:global_step/sec: 47.3895\n",
      "INFO:tensorflow:loss = 0.000253935, step = 6801\n",
      "INFO:tensorflow:global_step/sec: 48.3606\n",
      "INFO:tensorflow:loss = 0.000294756, step = 6901\n",
      "INFO:tensorflow:global_step/sec: 48.2439\n",
      "INFO:tensorflow:loss = 0.000247637, step = 7001\n",
      "INFO:tensorflow:global_step/sec: 49.484\n",
      "INFO:tensorflow:loss = 0.000296135, step = 7101\n",
      "INFO:tensorflow:global_step/sec: 45.3401\n",
      "INFO:tensorflow:loss = 0.000239681, step = 7201\n",
      "INFO:tensorflow:global_step/sec: 49.1778\n",
      "INFO:tensorflow:loss = 0.000283993, step = 7301\n",
      "INFO:tensorflow:global_step/sec: 49.3039\n",
      "INFO:tensorflow:loss = 0.000228941, step = 7401\n",
      "INFO:tensorflow:global_step/sec: 48.5518\n",
      "INFO:tensorflow:loss = 0.000286593, step = 7501\n",
      "INFO:tensorflow:global_step/sec: 47.7636\n",
      "INFO:tensorflow:loss = 0.000220827, step = 7601\n",
      "INFO:tensorflow:global_step/sec: 45.2551\n",
      "INFO:tensorflow:loss = 0.00028506, step = 7701\n",
      "INFO:tensorflow:global_step/sec: 48.6444\n",
      "INFO:tensorflow:loss = 0.000212107, step = 7801\n",
      "INFO:tensorflow:global_step/sec: 49.5807\n",
      "INFO:tensorflow:loss = 0.000265663, step = 7901\n",
      "INFO:tensorflow:global_step/sec: 48.1462\n",
      "INFO:tensorflow:loss = 0.00022177, step = 8001\n",
      "INFO:tensorflow:global_step/sec: 48.3057\n",
      "INFO:tensorflow:loss = 0.00022225, step = 8101\n",
      "INFO:tensorflow:global_step/sec: 37.6548\n",
      "INFO:tensorflow:loss = 0.000247993, step = 8201\n",
      "INFO:tensorflow:global_step/sec: 32.695\n",
      "INFO:tensorflow:loss = 0.000199172, step = 8301\n",
      "INFO:tensorflow:global_step/sec: 33.9753\n",
      "INFO:tensorflow:loss = 0.000268726, step = 8401\n",
      "INFO:tensorflow:global_step/sec: 49.1519\n",
      "INFO:tensorflow:loss = 0.0001938, step = 8501\n",
      "INFO:tensorflow:global_step/sec: 41.5684\n",
      "INFO:tensorflow:loss = 0.000251399, step = 8601\n",
      "INFO:tensorflow:global_step/sec: 41.6179\n",
      "INFO:tensorflow:loss = 0.00019787, step = 8701\n",
      "INFO:tensorflow:global_step/sec: 48.821\n",
      "INFO:tensorflow:loss = 0.000219011, step = 8801\n",
      "INFO:tensorflow:global_step/sec: 43.017\n",
      "INFO:tensorflow:loss = 0.000207198, step = 8901\n",
      "INFO:tensorflow:global_step/sec: 49.0102\n",
      "INFO:tensorflow:loss = 0.000192793, step = 9001\n",
      "INFO:tensorflow:global_step/sec: 41.9638\n",
      "INFO:tensorflow:loss = 0.000222248, step = 9101\n",
      "INFO:tensorflow:global_step/sec: 36.7671\n",
      "INFO:tensorflow:loss = 0.000175754, step = 9201\n",
      "INFO:tensorflow:global_step/sec: 39.5895\n",
      "INFO:tensorflow:loss = 0.000251505, step = 9301\n",
      "INFO:tensorflow:global_step/sec: 46.567\n",
      "INFO:tensorflow:loss = 0.000171777, step = 9401\n",
      "INFO:tensorflow:global_step/sec: 49.4024\n",
      "INFO:tensorflow:loss = 0.000219957, step = 9501\n",
      "INFO:tensorflow:global_step/sec: 46.1793\n",
      "INFO:tensorflow:loss = 0.000184232, step = 9601\n",
      "INFO:tensorflow:global_step/sec: 48.8789\n",
      "INFO:tensorflow:loss = 0.000181853, step = 9701\n",
      "INFO:tensorflow:global_step/sec: 39.0218\n",
      "INFO:tensorflow:loss = 0.00020671, step = 9801\n",
      "INFO:tensorflow:global_step/sec: 45.8835\n",
      "INFO:tensorflow:loss = 0.000158989, step = 9901\n",
      "INFO:tensorflow:global_step/sec: 37.9327\n",
      "INFO:tensorflow:Saving checkpoints for 10000 into /var/folders/5x/z33hrhcn4tqfk2tk0d1ffp4w0000gn/T/tmpW1MmPy/model.ckpt.\n",
      "WARNING:tensorflow:*******************************************************\n",
      "WARNING:tensorflow:TensorFlow's V1 checkpoint format has been deprecated.\n",
      "WARNING:tensorflow:Consider switching to the more efficient V2 format:\n",
      "WARNING:tensorflow:   `tf.train.Saver(write_version=tf.train.SaverDef.V2)`\n",
      "WARNING:tensorflow:now on by default.\n",
      "WARNING:tensorflow:*******************************************************\n",
      "INFO:tensorflow:Loss for final step: 0.000229665.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "DNNRegressor(hidden_units=[100, 100, 100, 100], dropout=None, optimizer=None, feature_columns=[_RealValuedColumn(column_name='LotFrontage', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='LotArea', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='OverallQual', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='OverallCond', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='YearBuilt', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='YearRemodAdd', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='MasVnrArea', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='ExterQual', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='ExterCond', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='BsmtQual', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='BsmtCond', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='BsmtExposure', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='BsmtFinType1', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='BsmtFinSF1', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='BsmtFinType2', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='BsmtFinSF2', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='BsmtUnfSF', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='TotalBsmtSF', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='HeatingQC', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='1stFlrSF', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='2ndFlrSF', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='LowQualFinSF', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='GrLivArea', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='BsmtFullBath', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='BsmtHalfBath', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='FullBath', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='HalfBath', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='BedroomAbvGr', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='KitchenAbvGr', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='KitchenQual', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='TotRmsAbvGrd', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='Functional', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='Fireplaces', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='FireplaceQu', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='GarageYrBlt', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='GarageFinish', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='GarageCars', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='GarageArea', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='GarageQual', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='GarageCond', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='WoodDeckSF', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='OpenPorchSF', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='EnclosedPorch', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='3SsnPorch', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='ScreenPorch', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='PoolArea', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='PoolQC', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='MiscVal', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='MoSold', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _RealValuedColumn(column_name='YrSold', dimension=1, default_value=None, dtype=tf.float32, normalizer=None), _OneHotColumn(sparse_id_column=_SparseColumn(column_name='MSSubClass', is_integerized=False, bucket_size=None, lookup_config=_SparseIdLookupConfig(vocabulary_file=None, keys=('class20', 'class60', 'class50', 'class120', 'class30', 'class160', 'class70', 'class80', 'class90', 'class190', 'class85', 'class75', 'class45', 'class180', 'class40'), num_oov_buckets=0, vocab_size=15, default_value=-1), combiner='sum', dtype=tf.string)), _OneHotColumn(sparse_id_column=_SparseColumn(column_name='MSZoning', is_integerized=False, bucket_size=None, lookup_config=_SparseIdLookupConfig(vocabulary_file=None, keys=('RL', 'RM', 'FV', 'RH', 'C', 'None'), num_oov_buckets=0, vocab_size=6, default_value=-1), combiner='sum', dtype=tf.string)), _OneHotColumn(sparse_id_column=_SparseColumn(column_name='Street', is_integerized=False, bucket_size=None, lookup_config=_SparseIdLookupConfig(vocabulary_file=None, keys=('Pave', 'Grvl'), num_oov_buckets=0, vocab_size=2, default_value=-1), combiner='sum', dtype=tf.string)), _OneHotColumn(sparse_id_column=_SparseColumn(column_name='Alley', is_integerized=False, bucket_size=None, lookup_config=_SparseIdLookupConfig(vocabulary_file=None, keys=('NoAlley', 'Grvl', 'Pave'), num_oov_buckets=0, vocab_size=3, default_value=-1), combiner='sum', dtype=tf.string)), _OneHotColumn(sparse_id_column=_SparseColumn(column_name='LotShape', is_integerized=False, bucket_size=None, lookup_config=_SparseIdLookupConfig(vocabulary_file=None, keys=('Reg', 'IR1', 'IR2', 'IR3'), num_oov_buckets=0, vocab_size=4, default_value=-1), combiner='sum', dtype=tf.string)), _OneHotColumn(sparse_id_column=_SparseColumn(column_name='LandContour', is_integerized=False, bucket_size=None, lookup_config=_SparseIdLookupConfig(vocabulary_file=None, keys=('Lvl', 'Bnk', 'HLS', 'Low'), num_oov_buckets=0, vocab_size=4, default_value=-1), combiner='sum', dtype=tf.string)), _OneHotColumn(sparse_id_column=_SparseColumn(column_name='Utilities', is_integerized=False, bucket_size=None, lookup_config=_SparseIdLookupConfig(vocabulary_file=None, keys=('AllPub', 'NoSeWa', 'None'), num_oov_buckets=0, vocab_size=3, default_value=-1), combiner='sum', dtype=tf.string)), _OneHotColumn(sparse_id_column=_SparseColumn(column_name='LotConfig', is_integerized=False, bucket_size=None, lookup_config=_SparseIdLookupConfig(vocabulary_file=None, keys=('Inside', 'Corner', 'CulDSac', 'FR2', 'FR3'), num_oov_buckets=0, vocab_size=5, default_value=-1), combiner='sum', dtype=tf.string)), _OneHotColumn(sparse_id_column=_SparseColumn(column_name='LandSlope', is_integerized=False, bucket_size=None, lookup_config=_SparseIdLookupConfig(vocabulary_file=None, keys=('Gtl', 'Mod', 'Sev'), num_oov_buckets=0, vocab_size=3, default_value=-1), combiner='sum', dtype=tf.string)), _OneHotColumn(sparse_id_column=_SparseColumn(column_name='Neighborhood', is_integerized=False, bucket_size=None, lookup_config=_SparseIdLookupConfig(vocabulary_file=None, keys=('NAmes', 'CollgCr', 'OldTown', 'Edwards', 'Somerst', 'Gilbert', 'NridgHt', 'Sawyer', 'NWAmes', 'SawyerW', 'BrkSide', 'Crawfor', 'Mitchel', 'NoRidge', 'Timber', 'IDOTRR', 'ClearCr', 'SWISU', 'StoneBr', 'MeadowV', 'Blmngtn', 'BrDale', 'Veenker', 'NPkVill', 'Blueste'), num_oov_buckets=0, vocab_size=25, default_value=-1), combiner='sum', dtype=tf.string)), _OneHotColumn(sparse_id_column=_SparseColumn(column_name='Condition1', is_integerized=False, bucket_size=None, lookup_config=_SparseIdLookupConfig(vocabulary_file=None, keys=('Norm', 'Feedr', 'Artery', 'RRAn', 'PosN', 'RRAe', 'PosA', 'RRNn', 'RRNe'), num_oov_buckets=0, vocab_size=9, default_value=-1), combiner='sum', dtype=tf.string)), _OneHotColumn(sparse_id_column=_SparseColumn(column_name='Condition2', is_integerized=False, bucket_size=None, lookup_config=_SparseIdLookupConfig(vocabulary_file=None, keys=('Norm', 'Feedr', 'Artery', 'RRNn', 'PosN', 'RRAn', 'RRAe', 'PosA'), num_oov_buckets=0, vocab_size=8, default_value=-1), combiner='sum', dtype=tf.string)), _OneHotColumn(sparse_id_column=_SparseColumn(column_name='BldgType', is_integerized=False, bucket_size=None, lookup_config=_SparseIdLookupConfig(vocabulary_file=None, keys=('1Fam', 'TwnhsE', 'Duplex', 'Twnhs', '2fmCon'), num_oov_buckets=0, vocab_size=5, default_value=-1), combiner='sum', dtype=tf.string)), _OneHotColumn(sparse_id_column=_SparseColumn(column_name='HouseStyle', is_integerized=False, bucket_size=None, lookup_config=_SparseIdLookupConfig(vocabulary_file=None, keys=('1Story', '2Story', '1.5Fin', 'SLvl', 'SFoyer', '1.5Unf', '2.5Unf', '2.5Fin'), num_oov_buckets=0, vocab_size=8, default_value=-1), combiner='sum', dtype=tf.string)), _OneHotColumn(sparse_id_column=_SparseColumn(column_name='RoofStyle', is_integerized=False, bucket_size=None, lookup_config=_SparseIdLookupConfig(vocabulary_file=None, keys=('Gable', 'Hip', 'Flat', 'Gambrel', 'Mansard', 'Shed'), num_oov_buckets=0, vocab_size=6, default_value=-1), combiner='sum', dtype=tf.string)), _OneHotColumn(sparse_id_column=_SparseColumn(column_name='RoofMatl', is_integerized=False, bucket_size=None, lookup_config=_SparseIdLookupConfig(vocabulary_file=None, keys=('CompShg', 'Tar&Grv', 'WdShngl', 'WdShake', 'Membran', 'Metal', 'ClyTile', 'Roll'), num_oov_buckets=0, vocab_size=8, default_value=-1), combiner='sum', dtype=tf.string)), _OneHotColumn(sparse_id_column=_SparseColumn(column_name='Exterior1st', is_integerized=False, bucket_size=None, lookup_config=_SparseIdLookupConfig(vocabulary_file=None, keys=('VinylSd', 'HdBoard', 'MetalSd', 'Wd Sdng', 'Plywood', 'CemntBd', 'BrkFace', 'WdShing', 'Stucco', 'AsbShng', 'Stone', 'BrkComm', 'AsphShn', 'ImStucc', 'CBlock', 'None'), num_oov_buckets=0, vocab_size=16, default_value=-1), combiner='sum', dtype=tf.string)), _OneHotColumn(sparse_id_column=_SparseColumn(column_name='Exterior2nd', is_integerized=False, bucket_size=None, lookup_config=_SparseIdLookupConfig(vocabulary_file=None, keys=('VinylSd', 'MetalSd', 'HdBoard', 'Wd Sdng', 'Plywood', 'CmentBd', 'Wd Shng', 'Stucco', 'BrkFace', 'AsbShng', 'ImStucc', 'Brk Cmn', 'Stone', 'AsphShn', 'Other', 'CBlock', 'None'), num_oov_buckets=0, vocab_size=17, default_value=-1), combiner='sum', dtype=tf.string)), _OneHotColumn(sparse_id_column=_SparseColumn(column_name='MasVnrType', is_integerized=False, bucket_size=None, lookup_config=_SparseIdLookupConfig(vocabulary_file=None, keys=('None', 'BrkFace', 'Stone', 'BrkCmn', 'NoMasVnr'), num_oov_buckets=0, vocab_size=5, default_value=-1), combiner='sum', dtype=tf.string)), _OneHotColumn(sparse_id_column=_SparseColumn(column_name='Foundation', is_integerized=False, bucket_size=None, lookup_config=_SparseIdLookupConfig(vocabulary_file=None, keys=('PConc', 'CBlock', 'BrkTil', 'Slab', 'Stone', 'Wood'), num_oov_buckets=0, vocab_size=6, default_value=-1), combiner='sum', dtype=tf.string)), _OneHotColumn(sparse_id_column=_SparseColumn(column_name='Heating', is_integerized=False, bucket_size=None, lookup_config=_SparseIdLookupConfig(vocabulary_file=None, keys=('GasA', 'GasW', 'Grav', 'Wall', 'OthW', 'Floor'), num_oov_buckets=0, vocab_size=6, default_value=-1), combiner='sum', dtype=tf.string)), _OneHotColumn(sparse_id_column=_SparseColumn(column_name='CentralAir', is_integerized=False, bucket_size=None, lookup_config=_SparseIdLookupConfig(vocabulary_file=None, keys=('Y', 'N'), num_oov_buckets=0, vocab_size=2, default_value=-1), combiner='sum', dtype=tf.string)), _OneHotColumn(sparse_id_column=_SparseColumn(column_name='Electrical', is_integerized=False, bucket_size=None, lookup_config=_SparseIdLookupConfig(vocabulary_file=None, keys=('SBrkr', 'FuseA', 'FuseF', 'FuseP', 'Mix', 'NoElec'), num_oov_buckets=0, vocab_size=6, default_value=-1), combiner='sum', dtype=tf.string)), _OneHotColumn(sparse_id_column=_SparseColumn(column_name='GarageType', is_integerized=False, bucket_size=None, lookup_config=_SparseIdLookupConfig(vocabulary_file=None, keys=('Attchd', 'Detchd', 'BuiltIn', 'NoGarage', 'Basment', 'CarPort', '2Types'), num_oov_buckets=0, vocab_size=7, default_value=-1), combiner='sum', dtype=tf.string)), _OneHotColumn(sparse_id_column=_SparseColumn(column_name='PavedDrive', is_integerized=False, bucket_size=None, lookup_config=_SparseIdLookupConfig(vocabulary_file=None, keys=('Y', 'N', 'P'), num_oov_buckets=0, vocab_size=3, default_value=-1), combiner='sum', dtype=tf.string)), _OneHotColumn(sparse_id_column=_SparseColumn(column_name='Fence', is_integerized=False, bucket_size=None, lookup_config=_SparseIdLookupConfig(vocabulary_file=None, keys=('NoFc', 'MnPrv', 'GdPrv', 'GdWo', 'MnWw'), num_oov_buckets=0, vocab_size=5, default_value=-1), combiner='sum', dtype=tf.string)), _OneHotColumn(sparse_id_column=_SparseColumn(column_name='MiscFeature', is_integerized=False, bucket_size=None, lookup_config=_SparseIdLookupConfig(vocabulary_file=None, keys=('NoFtr', 'Shed', 'Othr', 'Gar2', 'TenC'), num_oov_buckets=0, vocab_size=5, default_value=-1), combiner='sum', dtype=tf.string)), _OneHotColumn(sparse_id_column=_SparseColumn(column_name='SaleType', is_integerized=False, bucket_size=None, lookup_config=_SparseIdLookupConfig(vocabulary_file=None, keys=('WD', 'New', 'COD', 'ConLD', 'ConLw', 'ConLI', 'CWD', 'Oth', 'Con', 'None'), num_oov_buckets=0, vocab_size=10, default_value=-1), combiner='sum', dtype=tf.string)), _OneHotColumn(sparse_id_column=_SparseColumn(column_name='SaleCondition', is_integerized=False, bucket_size=None, lookup_config=_SparseIdLookupConfig(vocabulary_file=None, keys=('Normal', 'Partial', 'Abnorml', 'Family', 'Alloca', 'AdjLand'), num_oov_buckets=0, vocab_size=6, default_value=-1), combiner='sum', dtype=tf.string))])"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Training the Regressor\n",
    "regressor.fit(input_fn=lambda: input_pdtotf(train_normal,True), steps=10000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "INFO:tensorflow:Summary name dnn/hiddenlayer_0:fraction_of_zero_values is illegal; using dnn/hiddenlayer_0_fraction_of_zero_values instead.\n",
      "INFO:tensorflow:Summary name dnn/hiddenlayer_0:activation is illegal; using dnn/hiddenlayer_0_activation instead.\n",
      "INFO:tensorflow:Summary name dnn/hiddenlayer_1:fraction_of_zero_values is illegal; using dnn/hiddenlayer_1_fraction_of_zero_values instead.\n",
      "INFO:tensorflow:Summary name dnn/hiddenlayer_1:activation is illegal; using dnn/hiddenlayer_1_activation instead.\n",
      "INFO:tensorflow:Summary name dnn/hiddenlayer_2:fraction_of_zero_values is illegal; using dnn/hiddenlayer_2_fraction_of_zero_values instead.\n",
      "INFO:tensorflow:Summary name dnn/hiddenlayer_2:activation is illegal; using dnn/hiddenlayer_2_activation instead.\n",
      "INFO:tensorflow:Summary name dnn/hiddenlayer_3:fraction_of_zero_values is illegal; using dnn/hiddenlayer_3_fraction_of_zero_values instead.\n",
      "INFO:tensorflow:Summary name dnn/hiddenlayer_3:activation is illegal; using dnn/hiddenlayer_3_activation instead.\n",
      "INFO:tensorflow:Summary name logits:fraction_of_zero_values is illegal; using logits_fraction_of_zero_values instead.\n",
      "INFO:tensorflow:Summary name logits:activation is illegal; using logits_activation instead.\n",
      "INFO:tensorflow:Restored model from /var/folders/5x/z33hrhcn4tqfk2tk0d1ffp4w0000gn/T/tmpW1MmPy\n",
      "INFO:tensorflow:Eval steps [0,1) for training step 10000.\n",
      "INFO:tensorflow:Saving evaluation summary for step 10000: loss = 0.000203351\n",
      "Loss: 0.000203\n"
     ]
    }
   ],
   "source": [
    "#Evaluating the Model\n",
    "raw_cv = raw_test = pd.read_csv(folder+\"train_cv2.csv\")\n",
    "cv = input_clean(raw_cv)\n",
    "cv_normal = input_normalize(cv,True)\n",
    "ev = regressor.evaluate(input_fn=lambda: input_pdtotf(cv_normal ,True), steps=1)\n",
    "\n",
    "loss_score = ev[\"loss\"]\n",
    "print(\"Loss: {0:f}\".format(loss_score))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From /Users/lanxing/.local/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/dnn_linear_combined.py:1053 in predict.: calling predict (from tensorflow.contrib.learn.python.learn.estimators.estimator) with x is deprecated and will be removed after 2016-12-01.\n",
      "Instructions for updating:\n",
      "Estimator is decoupled from Scikit Learn interface by moving into\n",
      "separate class SKCompat. Arguments x, y and batch_size are only\n",
      "available in the SKCompat class, Estimator will only accept input_fn.\n",
      "Example conversion:\n",
      "  est = Estimator(...) -> est = SKCompat(Estimator(...))\n",
      "WARNING:tensorflow:From /Users/lanxing/.local/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/dnn_linear_combined.py:1053 in predict.: calling predict (from tensorflow.contrib.learn.python.learn.estimators.estimator) with batch_size is deprecated and will be removed after 2016-12-01.\n",
      "Instructions for updating:\n",
      "Estimator is decoupled from Scikit Learn interface by moving into\n",
      "separate class SKCompat. Arguments x, y and batch_size are only\n",
      "available in the SKCompat class, Estimator will only accept input_fn.\n",
      "Example conversion:\n",
      "  est = Estimator(...) -> est = SKCompat(Estimator(...))\n",
      "WARNING:tensorflow:From /Users/lanxing/.local/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/dnn_linear_combined.py:1053 in predict.: calling predict (from tensorflow.contrib.learn.python.learn.estimators.estimator) with as_iterable is deprecated and will be removed after 2016-12-01.\n",
      "Instructions for updating:\n",
      "Estimator is decoupled from Scikit Learn interface by moving into\n",
      "separate class SKCompat. Arguments x, y and batch_size are only\n",
      "available in the SKCompat class, Estimator will only accept input_fn.\n",
      "Example conversion:\n",
      "  est = Estimator(...) -> est = SKCompat(Estimator(...))\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "WARNING:tensorflow:Rank of input Tensor (1) should be the same as output_rank (2) for column. Will attempt to expand dims. It is highly recommended that you resize your input, as this behavior may change.\n",
      "INFO:tensorflow:Summary name dnn/hiddenlayer_0:fraction_of_zero_values is illegal; using dnn/hiddenlayer_0_fraction_of_zero_values instead.\n",
      "INFO:tensorflow:Summary name dnn/hiddenlayer_0:activation is illegal; using dnn/hiddenlayer_0_activation instead.\n",
      "INFO:tensorflow:Summary name dnn/hiddenlayer_1:fraction_of_zero_values is illegal; using dnn/hiddenlayer_1_fraction_of_zero_values instead.\n",
      "INFO:tensorflow:Summary name dnn/hiddenlayer_1:activation is illegal; using dnn/hiddenlayer_1_activation instead.\n",
      "INFO:tensorflow:Summary name dnn/hiddenlayer_2:fraction_of_zero_values is illegal; using dnn/hiddenlayer_2_fraction_of_zero_values instead.\n",
      "INFO:tensorflow:Summary name dnn/hiddenlayer_2:activation is illegal; using dnn/hiddenlayer_2_activation instead.\n",
      "INFO:tensorflow:Summary name dnn/hiddenlayer_3:fraction_of_zero_values is illegal; using dnn/hiddenlayer_3_fraction_of_zero_values instead.\n",
      "INFO:tensorflow:Summary name dnn/hiddenlayer_3:activation is illegal; using dnn/hiddenlayer_3_activation instead.\n",
      "INFO:tensorflow:Summary name logits:fraction_of_zero_values is illegal; using logits_fraction_of_zero_values instead.\n",
      "INFO:tensorflow:Summary name logits:activation is illegal; using logits_activation instead.\n",
      "INFO:tensorflow:Loading model from checkpoint: /var/folders/5x/z33hrhcn4tqfk2tk0d1ffp4w0000gn/T/tmplrBDZJ/model.ckpt-10000-?????-of-00001.\n",
      "                  0\n",
      "0     124140.925166\n",
      "1     147319.760266\n",
      "2     193241.028100\n",
      "3     202022.684121\n",
      "4     176716.647699\n",
      "5     179572.760078\n",
      "6     145958.832997\n",
      "7     171810.227516\n",
      "8     173091.643068\n",
      "9     144913.141251\n",
      "10    224905.662668\n",
      "11    123658.516527\n",
      "12    100908.282845\n",
      "13    142584.832156\n",
      "14     97121.244924\n",
      "15    314389.114666\n",
      "16    249006.812224\n",
      "17    269096.279114\n",
      "18    265098.331267\n",
      "19    470986.808133\n",
      "20    320771.662900\n",
      "21    181762.089989\n",
      "22    187665.679383\n",
      "23    161224.846587\n",
      "24    173797.226396\n",
      "25    185507.285003\n",
      "26    354263.822240\n",
      "27    218805.837068\n",
      "28    180117.710423\n",
      "29    252531.574148\n",
      "...             ...\n",
      "1429   89216.809163\n",
      "1430  150996.742597\n",
      "1431   87769.529594\n",
      "1432   94897.132661\n",
      "1433   71494.189334\n",
      "1434  406120.355392\n",
      "1435  282893.954870\n",
      "1436  182230.897939\n",
      "1437  147185.802874\n",
      "1438  206562.792429\n",
      "1439  136120.486645\n",
      "1440  191049.959877\n",
      "1441  183996.916482\n",
      "1442  280039.924175\n",
      "1443  372269.223720\n",
      "1444   94617.494996\n",
      "1445  188506.765270\n",
      "1446  113805.566201\n",
      "1447  122498.498520\n",
      "1448  159113.751484\n",
      "1449   88907.276809\n",
      "1450   80675.930931\n",
      "1451  170771.510482\n",
      "1452   68659.462495\n",
      "1453   80893.434643\n",
      "1454   80835.517707\n",
      "1455   77745.339359\n",
      "1456  164506.652465\n",
      "1457  113571.564613\n",
      "1458  203148.552865\n",
      "\n",
      "[1459 rows x 1 columns]\n"
     ]
    }
   ],
   "source": [
    "raw_test = pd.read_csv(folder+\"test.csv\")\n",
    "test_size = raw_test.shape[0]\n",
    "test = input_clean(raw_test)\n",
    "if \"SalePrice\" in test.columns:\n",
    "    test_normal = input_normalize(test,True).drop(\"SalePrice\",1)\n",
    "else:\n",
    "    test_normal = input_normalize(test,False)\n",
    "#for k in test_normal.columns:\n",
    "#    print(k,test_normal[k].isnull().sum())\n",
    "#test_normal.isnull().values.any()    \n",
    "y = regressor.predict(input_fn=lambda: input_pdtotf(test_normal,False))\n",
    "predictions_scaled = list(itertools.islice(y, test_size))\n",
    "#print (\"Predictions: {}\".format(str(predictions_scaled)))\n",
    "predictions = pd.DataFrame(predictions_scaled) * price_range + price_offset\n",
    "print(predictions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "result_list = predictions[0].tolist()\n",
    "id = 1461\n",
    "filename = \"result/lx_result3.csv\"\n",
    "with open(folder+filename, 'wb') as csvfile:\n",
    "    fieldnames = ['Id', 'SalePrice']\n",
    "    writer = csv.DictWriter(csvfile, fieldnames=fieldnames)\n",
    "\n",
    "    writer.writeheader()\n",
    "    for row in result_list:\n",
    "        writer.writerow({'Id': str(id), 'SalePrice': str(row)})\n",
    "        id=id+1\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     MSSubClass MSZoning  LotFrontage  LotArea Street\n",
      "447     class60       RL          0.0    11214   Pave\n",
      "716     class70       RM         60.0    10800   Pave\n",
      "170     class50       RM          0.0    12358   Pave\n",
      "984     class90       RL         75.0    10125   Pave\n",
      "321     class60       RL         99.0    12099   Pave\n",
      "214     class60       RL          0.0    10900   Pave\n",
      "467     class70       RL         79.0     9480   Pave\n",
      "416     class60       RL         74.0     7844   Pave\n",
      "998     class30       RM         60.0     9786   Pave\n",
      "536     class60       RL         57.0     8924   Pave\n",
      "337     class20       RL         70.0     9135   Pave\n",
      "874     class50       RM         52.0     5720   Pave\n",
      "186     class80       RL          0.0     9947   Pave\n",
      "334     class60       RL         59.0     9042   Pave\n",
      "824     class20       FV         81.0    11216   Pave\n",
      "725     class20       RL         60.0     6960   Pave\n",
      "1135    class30       RM         60.0     6180   Pave\n",
      "397     class60       RL         69.0     7590   Pave\n",
      "289     class70       RL         60.0     8730   Pave\n",
      "717     class20       RL         80.0    10000   Pave\n",
      "577     class80       RL         96.0    11777   Pave\n",
      "1247    class80       RL          0.0    12328   Pave\n",
      "396     class20       RL         60.0     7200   Pave\n",
      "1186   class190       RL        107.0    10615   Pave\n",
      "873     class40       RL         60.0    12144   Pave\n",
      "1254    class60       RL         60.0     6931   Pave\n",
      "307     class50       RM          0.0     7920   Pave\n",
      "1039   class180       RM         21.0     1477   Pave\n",
      "354     class50       RL         60.0     8400   Pave\n",
      "581     class20       RL         98.0    12704   Pave\n",
      "...         ...      ...          ...      ...    ...\n",
      "617     class45       RL         59.0     7227   Pave\n",
      "703    class190       RM         76.0     7630   Pave\n",
      "318     class60       RL         90.0     9900   Pave\n",
      "697     class20       RL         57.0     6420   Pave\n",
      "242     class50       RM         63.0     5000   Pave\n",
      "928     class20       RL          0.0    11838   Pave\n",
      "620     class30       RL         45.0     8248   Pave\n",
      "339     class20       RL         66.0    12400   Pave\n",
      "1242    class85       RL         85.0    10625   Pave\n",
      "712    class120       RL         40.0     4671   Pave\n",
      "964     class60       RL         80.0    11316   Pave\n",
      "341     class20       RH         60.0     8400   Pave\n",
      "509     class20       RL         80.0     9600   Pave\n",
      "892     class20       RL         70.0     8414   Pave\n",
      "727     class20       RL         64.0     7314   Pave\n",
      "227    class160       RM         21.0     1869   Pave\n",
      "645     class20       RL          0.0    10530   Pave\n",
      "528     class30       RL         58.0     9098   Pave\n",
      "136     class20       RL          0.0    10355   Pave\n",
      "498     class20       RL         65.0     7800   Pave\n",
      "565     class70       RL         66.0     6858   Pave\n",
      "129     class20       RL         69.0     8973   Pave\n",
      "740     class70       RM         60.0     9600   Pave\n",
      "1263    class70       RL         60.0    13515   Pave\n",
      "1087    class60       FV         85.0    10574   Pave\n",
      "846     class60       RL         75.0     9317   Pave\n",
      "1439    class60       RL         80.0    11584   Pave\n",
      "256     class60       FV         64.0     8791   Pave\n",
      "840     class70       RH          0.0    12155   Pave\n",
      "1325    class30       RM         40.0     3636   Pave\n",
      "\n",
      "[291 rows x 5 columns]\n"
     ]
    }
   ],
   "source": [
    "raw_train_size = raw_train.shape[0]\n",
    "use_rate = 0.8\n",
    "rows = random.sample(train.index, int(raw_train_size*(1-use_rate)))\n",
    "\n",
    "train_del = train.ix[rows]\n",
    "\n",
    "train_rest = train.drop(rows)\n",
    "print (train_del.iloc[:,0:5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   MSSubClass MSZoning  LotFrontage  LotArea Street\n",
      "1     class20       RL         80.0     9600   Pave\n",
      "2     class60       RL         68.0    11250   Pave\n",
      "3     class70       RL         60.0     9550   Pave\n",
      "4     class60       RL         84.0    14260   Pave\n",
      "5     class50       RL         85.0    14115   Pave\n",
      "6     class20       RL         75.0    10084   Pave\n",
      "7     class60       RL          0.0    10382   Pave\n",
      "8     class50       RM         51.0     6120   Pave\n",
      "9    class190       RL         50.0     7420   Pave\n",
      "11    class60       RL         85.0    11924   Pave\n",
      "12    class20       RL          0.0    12968   Pave\n",
      "13    class20       RL         91.0    10652   Pave\n",
      "14    class20       RL          0.0    10920   Pave\n",
      "15    class45       RM         51.0     6120   Pave\n",
      "16    class20       RL          0.0    11241   Pave\n",
      "19    class20       RL         70.0     7560   Pave\n",
      "20    class60       RL        101.0    14215   Pave\n",
      "21    class45       RM         57.0     7449   Pave\n",
      "22    class20       RL         75.0     9742   Pave\n",
      "23   class120       RM         44.0     4224   Pave\n"
     ]
    }
   ],
   "source": [
    "print(train_rest.iloc[0:20,0:5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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