report.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# The Prediction of Client Subscription to Bank Deposits"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "Danni Li ; Vanessa Pang; Zunquan Wang; Diane Xu; Zibo Shang"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When a client deposits money into a bank, the bank can use that same money to lend to other customers (Westpac., n.d). However, since clients can withdraw their money at any time, it makes it difficult for banks to budget how much they are allowed to lend out (Westpac., n.d). Therefore, offering term deposits is one of the many ways used to address this issue.\n",
    "\n",
    "A term deposit is an investment where the client is guaranteed a specific return rate at the end of a fixed-term after depositing funds into a bank (Chen, 2021). By investing in these accounts, the client agrees to not withdraw their funds for a specific time frame in return for a higher interest rate (Westpac., n.d). One of the many benefits includes that if interest rates shift lower over time, the client will still earn the fixed interest rate on the maturity date (Chen, 2021). Banks have often been interested in knowing what type of clients will subscribe to term deposits. Therefore, this data analysis project will address the question, **“Given a new client, will they subscribe to a term deposit?”**\n",
    "\n",
    "The dataset used to explore the above question is taken from the UCI Machine Learning Repository and is titled bank-additional-full.csv. This file includes 41188 observations, ranging from May 2008 to November 2010, and 20 input variables. The target variable is y, a boolean: Yes if the client subscribes to a term deposit, and No otherwise. Of the 41188 observations, 5289 clients are subscribed to a term deposit, and 39922 are not subscribed.\n",
    "\n",
    "<img align=\"centre\" src=\"intro_pic.jpeg\" width=\"750\" />\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "── \u001b[1mAttaching packages\u001b[22m ─────────────────────────────────────── tidyverse 1.3.0 ──\n",
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      "\n"
     ]
    }
   ],
   "source": [
    "### Run this cell before continuing.\n",
    "library(tidyverse)\n",
    "library(repr)\n",
    "library(tidymodels)\n",
    "options(repr.matrix.max.rows = 6)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Pre-Processing\n",
    "The following cells downloads the data file from UCI website directly so this could run in any environment. The expected outcome `y` is then mutated into a factor."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A data.frame: 45211 × 17</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>age</th><th scope=col>job</th><th scope=col>marital</th><th scope=col>education</th><th scope=col>default</th><th scope=col>balance</th><th scope=col>housing</th><th scope=col>loan</th><th scope=col>contact</th><th scope=col>day</th><th scope=col>month</th><th scope=col>duration</th><th scope=col>campaign</th><th scope=col>pdays</th><th scope=col>previous</th><th scope=col>poutcome</th><th scope=col>y</th></tr>\n",
       "\t<tr><th scope=col>&lt;int&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;fct&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>58</td><td>management  </td><td>married</td><td>tertiary </td><td>no</td><td>2143</td><td>yes</td><td>no </td><td>unknown</td><td>5</td><td>may</td><td>261</td><td>1</td><td>-1</td><td>0</td><td>unknown</td><td>no</td></tr>\n",
       "\t<tr><td>44</td><td>technician  </td><td>single </td><td>secondary</td><td>no</td><td>  29</td><td>yes</td><td>no </td><td>unknown</td><td>5</td><td>may</td><td>151</td><td>1</td><td>-1</td><td>0</td><td>unknown</td><td>no</td></tr>\n",
       "\t<tr><td>33</td><td>entrepreneur</td><td>married</td><td>secondary</td><td>no</td><td>   2</td><td>yes</td><td>yes</td><td>unknown</td><td>5</td><td>may</td><td> 76</td><td>1</td><td>-1</td><td>0</td><td>unknown</td><td>no</td></tr>\n",
       "\t<tr><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td></tr>\n",
       "\t<tr><td>72</td><td>retired     </td><td>married</td><td>secondary</td><td>no</td><td>5715</td><td>no</td><td>no</td><td>cellular </td><td>17</td><td>nov</td><td>1127</td><td>5</td><td>184</td><td> 3</td><td>success</td><td>yes</td></tr>\n",
       "\t<tr><td>57</td><td>blue-collar </td><td>married</td><td>secondary</td><td>no</td><td> 668</td><td>no</td><td>no</td><td>telephone</td><td>17</td><td>nov</td><td> 508</td><td>4</td><td> -1</td><td> 0</td><td>unknown</td><td>no </td></tr>\n",
       "\t<tr><td>37</td><td>entrepreneur</td><td>married</td><td>secondary</td><td>no</td><td>2971</td><td>no</td><td>no</td><td>cellular </td><td>17</td><td>nov</td><td> 361</td><td>2</td><td>188</td><td>11</td><td>other  </td><td>no </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 45211 × 17\n",
       "\\begin{tabular}{lllllllllllllllll}\n",
       " age & job & marital & education & default & balance & housing & loan & contact & day & month & duration & campaign & pdays & previous & poutcome & y\\\\\n",
       " <int> & <fct> & <fct> & <fct> & <chr> & <int> & <fct> & <chr> & <chr> & <int> & <chr> & <int> & <int> & <int> & <int> & <chr> & <fct>\\\\\n",
       "\\hline\n",
       "\t 58 & management   & married & tertiary  & no & 2143 & yes & no  & unknown & 5 & may & 261 & 1 & -1 & 0 & unknown & no\\\\\n",
       "\t 44 & technician   & single  & secondary & no &   29 & yes & no  & unknown & 5 & may & 151 & 1 & -1 & 0 & unknown & no\\\\\n",
       "\t 33 & entrepreneur & married & secondary & no &    2 & yes & yes & unknown & 5 & may &  76 & 1 & -1 & 0 & unknown & no\\\\\n",
       "\t ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮\\\\\n",
       "\t 72 & retired      & married & secondary & no & 5715 & no & no & cellular  & 17 & nov & 1127 & 5 & 184 &  3 & success & yes\\\\\n",
       "\t 57 & blue-collar  & married & secondary & no &  668 & no & no & telephone & 17 & nov &  508 & 4 &  -1 &  0 & unknown & no \\\\\n",
       "\t 37 & entrepreneur & married & secondary & no & 2971 & no & no & cellular  & 17 & nov &  361 & 2 & 188 & 11 & other   & no \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 45211 × 17\n",
       "\n",
       "| age &lt;int&gt; | job &lt;fct&gt; | marital &lt;fct&gt; | education &lt;fct&gt; | default &lt;chr&gt; | balance &lt;int&gt; | housing &lt;fct&gt; | loan &lt;chr&gt; | contact &lt;chr&gt; | day &lt;int&gt; | month &lt;chr&gt; | duration &lt;int&gt; | campaign &lt;int&gt; | pdays &lt;int&gt; | previous &lt;int&gt; | poutcome &lt;chr&gt; | y &lt;fct&gt; |\n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| 58 | management   | married | tertiary  | no | 2143 | yes | no  | unknown | 5 | may | 261 | 1 | -1 | 0 | unknown | no |\n",
       "| 44 | technician   | single  | secondary | no |   29 | yes | no  | unknown | 5 | may | 151 | 1 | -1 | 0 | unknown | no |\n",
       "| 33 | entrepreneur | married | secondary | no |    2 | yes | yes | unknown | 5 | may |  76 | 1 | -1 | 0 | unknown | no |\n",
       "| ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ |\n",
       "| 72 | retired      | married | secondary | no | 5715 | no | no | cellular  | 17 | nov | 1127 | 5 | 184 |  3 | success | yes |\n",
       "| 57 | blue-collar  | married | secondary | no |  668 | no | no | telephone | 17 | nov |  508 | 4 |  -1 |  0 | unknown | no  |\n",
       "| 37 | entrepreneur | married | secondary | no | 2971 | no | no | cellular  | 17 | nov |  361 | 2 | 188 | 11 | other   | no  |\n",
       "\n"
      ],
      "text/plain": [
       "      age job          marital education default balance housing loan contact  \n",
       "1     58  management   married tertiary  no      2143    yes     no   unknown  \n",
       "2     44  technician   single  secondary no        29    yes     no   unknown  \n",
       "3     33  entrepreneur married secondary no         2    yes     yes  unknown  \n",
       "⋮     ⋮   ⋮            ⋮       ⋮         ⋮       ⋮       ⋮       ⋮    ⋮        \n",
       "45209 72  retired      married secondary no      5715    no      no   cellular \n",
       "45210 57  blue-collar  married secondary no       668    no      no   telephone\n",
       "45211 37  entrepreneur married secondary no      2971    no      no   cellular \n",
       "      day month duration campaign pdays previous poutcome y  \n",
       "1     5   may   261      1        -1    0        unknown  no \n",
       "2     5   may   151      1        -1    0        unknown  no \n",
       "3     5   may    76      1        -1    0        unknown  no \n",
       "⋮     ⋮   ⋮     ⋮        ⋮        ⋮     ⋮        ⋮        ⋮  \n",
       "45209 17  nov   1127     5        184    3       success  yes\n",
       "45210 17  nov    508     4         -1    0       unknown  no \n",
       "45211 17  nov    361     2        188   11       other    no "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#downloading zip file that contains dataset to local env\n",
    "download.file(\"http://archive.ics.uci.edu/ml/machine-learning-databases/00222/bank.zip\",\"bank.zip\")\n",
    "unzip(\"bank.zip\", \"bank-full.csv\") #unzip\n",
    "bank <- read.csv(\"bank-full.csv\", sep=\";\", header = TRUE) %>% \n",
    "        mutate(y = as_factor(y)) %>% #read csv and mutate outcome as factor for future traning\n",
    "        mutate(job = as_factor(job)) %>%\n",
    "        mutate(marital = as_factor(marital)) %>%\n",
    "        mutate(education = as_factor(education)) %>%\n",
    "        mutate(housing = as_factor(housing))\n",
    "bank"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A data.frame: 33909 × 17</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>age</th><th scope=col>job</th><th scope=col>marital</th><th scope=col>education</th><th scope=col>default</th><th scope=col>balance</th><th scope=col>housing</th><th scope=col>loan</th><th scope=col>contact</th><th scope=col>day</th><th scope=col>month</th><th scope=col>duration</th><th scope=col>campaign</th><th scope=col>pdays</th><th scope=col>previous</th><th scope=col>poutcome</th><th scope=col>y</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;fct&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>58</td><td>management  </td><td>married</td><td>tertiary </td><td>no</td><td>2143</td><td>yes</td><td>no </td><td>unknown</td><td>5</td><td>may</td><td>261</td><td>1</td><td>-1</td><td>0</td><td>unknown</td><td>no</td></tr>\n",
       "\t<tr><th scope=row>2</th><td>44</td><td>technician  </td><td>single </td><td>secondary</td><td>no</td><td>  29</td><td>yes</td><td>no </td><td>unknown</td><td>5</td><td>may</td><td>151</td><td>1</td><td>-1</td><td>0</td><td>unknown</td><td>no</td></tr>\n",
       "\t<tr><th scope=row>3</th><td>33</td><td>entrepreneur</td><td>married</td><td>secondary</td><td>no</td><td>   2</td><td>yes</td><td>yes</td><td>unknown</td><td>5</td><td>may</td><td> 76</td><td>1</td><td>-1</td><td>0</td><td>unknown</td><td>no</td></tr>\n",
       "\t<tr><th scope=row>⋮</th><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td></tr>\n",
       "\t<tr><th scope=row>45208</th><td>71</td><td>retired     </td><td>divorced</td><td>primary  </td><td>no</td><td>1729</td><td>no</td><td>no</td><td>cellular</td><td>17</td><td>nov</td><td> 456</td><td>2</td><td> -1</td><td> 0</td><td>unknown</td><td>yes</td></tr>\n",
       "\t<tr><th scope=row>45209</th><td>72</td><td>retired     </td><td>married </td><td>secondary</td><td>no</td><td>5715</td><td>no</td><td>no</td><td>cellular</td><td>17</td><td>nov</td><td>1127</td><td>5</td><td>184</td><td> 3</td><td>success</td><td>yes</td></tr>\n",
       "\t<tr><th scope=row>45211</th><td>37</td><td>entrepreneur</td><td>married </td><td>secondary</td><td>no</td><td>2971</td><td>no</td><td>no</td><td>cellular</td><td>17</td><td>nov</td><td> 361</td><td>2</td><td>188</td><td>11</td><td>other  </td><td>no </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 33909 × 17\n",
       "\\begin{tabular}{r|lllllllllllllllll}\n",
       "  & age & job & marital & education & default & balance & housing & loan & contact & day & month & duration & campaign & pdays & previous & poutcome & y\\\\\n",
       "  & <int> & <fct> & <fct> & <fct> & <chr> & <int> & <fct> & <chr> & <chr> & <int> & <chr> & <int> & <int> & <int> & <int> & <chr> & <fct>\\\\\n",
       "\\hline\n",
       "\t1 & 58 & management   & married & tertiary  & no & 2143 & yes & no  & unknown & 5 & may & 261 & 1 & -1 & 0 & unknown & no\\\\\n",
       "\t2 & 44 & technician   & single  & secondary & no &   29 & yes & no  & unknown & 5 & may & 151 & 1 & -1 & 0 & unknown & no\\\\\n",
       "\t3 & 33 & entrepreneur & married & secondary & no &    2 & yes & yes & unknown & 5 & may &  76 & 1 & -1 & 0 & unknown & no\\\\\n",
       "\t⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮\\\\\n",
       "\t45208 & 71 & retired      & divorced & primary   & no & 1729 & no & no & cellular & 17 & nov &  456 & 2 &  -1 &  0 & unknown & yes\\\\\n",
       "\t45209 & 72 & retired      & married  & secondary & no & 5715 & no & no & cellular & 17 & nov & 1127 & 5 & 184 &  3 & success & yes\\\\\n",
       "\t45211 & 37 & entrepreneur & married  & secondary & no & 2971 & no & no & cellular & 17 & nov &  361 & 2 & 188 & 11 & other   & no \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 33909 × 17\n",
       "\n",
       "| <!--/--> | age &lt;int&gt; | job &lt;fct&gt; | marital &lt;fct&gt; | education &lt;fct&gt; | default &lt;chr&gt; | balance &lt;int&gt; | housing &lt;fct&gt; | loan &lt;chr&gt; | contact &lt;chr&gt; | day &lt;int&gt; | month &lt;chr&gt; | duration &lt;int&gt; | campaign &lt;int&gt; | pdays &lt;int&gt; | previous &lt;int&gt; | poutcome &lt;chr&gt; | y &lt;fct&gt; |\n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| 1 | 58 | management   | married | tertiary  | no | 2143 | yes | no  | unknown | 5 | may | 261 | 1 | -1 | 0 | unknown | no |\n",
       "| 2 | 44 | technician   | single  | secondary | no |   29 | yes | no  | unknown | 5 | may | 151 | 1 | -1 | 0 | unknown | no |\n",
       "| 3 | 33 | entrepreneur | married | secondary | no |    2 | yes | yes | unknown | 5 | may |  76 | 1 | -1 | 0 | unknown | no |\n",
       "| ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ |\n",
       "| 45208 | 71 | retired      | divorced | primary   | no | 1729 | no | no | cellular | 17 | nov |  456 | 2 |  -1 |  0 | unknown | yes |\n",
       "| 45209 | 72 | retired      | married  | secondary | no | 5715 | no | no | cellular | 17 | nov | 1127 | 5 | 184 |  3 | success | yes |\n",
       "| 45211 | 37 | entrepreneur | married  | secondary | no | 2971 | no | no | cellular | 17 | nov |  361 | 2 | 188 | 11 | other   | no  |\n",
       "\n"
      ],
      "text/plain": [
       "      age job          marital  education default balance housing loan contact \n",
       "1     58  management   married  tertiary  no      2143    yes     no   unknown \n",
       "2     44  technician   single   secondary no        29    yes     no   unknown \n",
       "3     33  entrepreneur married  secondary no         2    yes     yes  unknown \n",
       "⋮     ⋮   ⋮            ⋮        ⋮         ⋮       ⋮       ⋮       ⋮    ⋮       \n",
       "45208 71  retired      divorced primary   no      1729    no      no   cellular\n",
       "45209 72  retired      married  secondary no      5715    no      no   cellular\n",
       "45211 37  entrepreneur married  secondary no      2971    no      no   cellular\n",
       "      day month duration campaign pdays previous poutcome y  \n",
       "1     5   may   261      1        -1    0        unknown  no \n",
       "2     5   may   151      1        -1    0        unknown  no \n",
       "3     5   may    76      1        -1    0        unknown  no \n",
       "⋮     ⋮   ⋮     ⋮        ⋮        ⋮     ⋮        ⋮        ⋮  \n",
       "45208 17  nov    456     2         -1    0       unknown  yes\n",
       "45209 17  nov   1127     5        184    3       success  yes\n",
       "45211 17  nov    361     2        188   11       other    no "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A data.frame: 11302 × 17</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>age</th><th scope=col>job</th><th scope=col>marital</th><th scope=col>education</th><th scope=col>default</th><th scope=col>balance</th><th scope=col>housing</th><th scope=col>loan</th><th scope=col>contact</th><th scope=col>day</th><th scope=col>month</th><th scope=col>duration</th><th scope=col>campaign</th><th scope=col>pdays</th><th scope=col>previous</th><th scope=col>poutcome</th><th scope=col>y</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;fct&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>7</th><td>28</td><td>management  </td><td>single  </td><td>tertiary</td><td>no </td><td>447</td><td>yes</td><td>yes</td><td>unknown</td><td>5</td><td>may</td><td>217</td><td>1</td><td>-1</td><td>0</td><td>unknown</td><td>no</td></tr>\n",
       "\t<tr><th scope=row>8</th><td>42</td><td>entrepreneur</td><td>divorced</td><td>tertiary</td><td>yes</td><td>  2</td><td>yes</td><td>no </td><td>unknown</td><td>5</td><td>may</td><td>380</td><td>1</td><td>-1</td><td>0</td><td>unknown</td><td>no</td></tr>\n",
       "\t<tr><th scope=row>9</th><td>58</td><td>retired     </td><td>married </td><td>primary </td><td>no </td><td>121</td><td>yes</td><td>no </td><td>unknown</td><td>5</td><td>may</td><td> 50</td><td>1</td><td>-1</td><td>0</td><td>unknown</td><td>no</td></tr>\n",
       "\t<tr><th scope=row>⋮</th><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td></tr>\n",
       "\t<tr><th scope=row>45206</th><td>25</td><td>technician </td><td>single </td><td>secondary</td><td>no</td><td>505</td><td>no</td><td>yes</td><td>cellular </td><td>17</td><td>nov</td><td>386</td><td>2</td><td>-1</td><td>0</td><td>unknown</td><td>yes</td></tr>\n",
       "\t<tr><th scope=row>45207</th><td>51</td><td>technician </td><td>married</td><td>tertiary </td><td>no</td><td>825</td><td>no</td><td>no </td><td>cellular </td><td>17</td><td>nov</td><td>977</td><td>3</td><td>-1</td><td>0</td><td>unknown</td><td>yes</td></tr>\n",
       "\t<tr><th scope=row>45210</th><td>57</td><td>blue-collar</td><td>married</td><td>secondary</td><td>no</td><td>668</td><td>no</td><td>no </td><td>telephone</td><td>17</td><td>nov</td><td>508</td><td>4</td><td>-1</td><td>0</td><td>unknown</td><td>no </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 11302 × 17\n",
       "\\begin{tabular}{r|lllllllllllllllll}\n",
       "  & age & job & marital & education & default & balance & housing & loan & contact & day & month & duration & campaign & pdays & previous & poutcome & y\\\\\n",
       "  & <int> & <fct> & <fct> & <fct> & <chr> & <int> & <fct> & <chr> & <chr> & <int> & <chr> & <int> & <int> & <int> & <int> & <chr> & <fct>\\\\\n",
       "\\hline\n",
       "\t7 & 28 & management   & single   & tertiary & no  & 447 & yes & yes & unknown & 5 & may & 217 & 1 & -1 & 0 & unknown & no\\\\\n",
       "\t8 & 42 & entrepreneur & divorced & tertiary & yes &   2 & yes & no  & unknown & 5 & may & 380 & 1 & -1 & 0 & unknown & no\\\\\n",
       "\t9 & 58 & retired      & married  & primary  & no  & 121 & yes & no  & unknown & 5 & may &  50 & 1 & -1 & 0 & unknown & no\\\\\n",
       "\t⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮\\\\\n",
       "\t45206 & 25 & technician  & single  & secondary & no & 505 & no & yes & cellular  & 17 & nov & 386 & 2 & -1 & 0 & unknown & yes\\\\\n",
       "\t45207 & 51 & technician  & married & tertiary  & no & 825 & no & no  & cellular  & 17 & nov & 977 & 3 & -1 & 0 & unknown & yes\\\\\n",
       "\t45210 & 57 & blue-collar & married & secondary & no & 668 & no & no  & telephone & 17 & nov & 508 & 4 & -1 & 0 & unknown & no \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 11302 × 17\n",
       "\n",
       "| <!--/--> | age &lt;int&gt; | job &lt;fct&gt; | marital &lt;fct&gt; | education &lt;fct&gt; | default &lt;chr&gt; | balance &lt;int&gt; | housing &lt;fct&gt; | loan &lt;chr&gt; | contact &lt;chr&gt; | day &lt;int&gt; | month &lt;chr&gt; | duration &lt;int&gt; | campaign &lt;int&gt; | pdays &lt;int&gt; | previous &lt;int&gt; | poutcome &lt;chr&gt; | y &lt;fct&gt; |\n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| 7 | 28 | management   | single   | tertiary | no  | 447 | yes | yes | unknown | 5 | may | 217 | 1 | -1 | 0 | unknown | no |\n",
       "| 8 | 42 | entrepreneur | divorced | tertiary | yes |   2 | yes | no  | unknown | 5 | may | 380 | 1 | -1 | 0 | unknown | no |\n",
       "| 9 | 58 | retired      | married  | primary  | no  | 121 | yes | no  | unknown | 5 | may |  50 | 1 | -1 | 0 | unknown | no |\n",
       "| ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ |\n",
       "| 45206 | 25 | technician  | single  | secondary | no | 505 | no | yes | cellular  | 17 | nov | 386 | 2 | -1 | 0 | unknown | yes |\n",
       "| 45207 | 51 | technician  | married | tertiary  | no | 825 | no | no  | cellular  | 17 | nov | 977 | 3 | -1 | 0 | unknown | yes |\n",
       "| 45210 | 57 | blue-collar | married | secondary | no | 668 | no | no  | telephone | 17 | nov | 508 | 4 | -1 | 0 | unknown | no  |\n",
       "\n"
      ],
      "text/plain": [
       "      age job          marital  education default balance housing loan\n",
       "7     28  management   single   tertiary  no      447     yes     yes \n",
       "8     42  entrepreneur divorced tertiary  yes       2     yes     no  \n",
       "9     58  retired      married  primary   no      121     yes     no  \n",
       "⋮     ⋮   ⋮            ⋮        ⋮         ⋮       ⋮       ⋮       ⋮   \n",
       "45206 25  technician   single   secondary no      505     no      yes \n",
       "45207 51  technician   married  tertiary  no      825     no      no  \n",
       "45210 57  blue-collar  married  secondary no      668     no      no  \n",
       "      contact   day month duration campaign pdays previous poutcome y  \n",
       "7     unknown   5   may   217      1        -1    0        unknown  no \n",
       "8     unknown   5   may   380      1        -1    0        unknown  no \n",
       "9     unknown   5   may    50      1        -1    0        unknown  no \n",
       "⋮     ⋮         ⋮   ⋮     ⋮        ⋮        ⋮     ⋮        ⋮        ⋮  \n",
       "45206 cellular  17  nov   386      2        -1    0        unknown  yes\n",
       "45207 cellular  17  nov   977      3        -1    0        unknown  yes\n",
       "45210 telephone 17  nov   508      4        -1    0        unknown  no "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Splitting the dataset into traning and testing set. Here we used a 8/2 split as normal practice.\n",
    "# 7.5/2.5 split provides a good balance of training and testing set sizes. \n",
    "bank_split <- initial_split(bank, prop = 0.75, strata = y)  \n",
    "bank_train <- training(bank_split)   \n",
    "bank_test <- testing(bank_split)\n",
    "\n",
    "bank_train\n",
    "bank_test"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Summarization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A data.frame: 1 × 3</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>Bought.Deposit</th><th scope=col>Did.not.Bought.Deposit</th><th scope=col>Total</th></tr>\n",
       "\t<tr><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>5289</td><td>39922</td><td>45211</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 1 × 3\n",
       "\\begin{tabular}{lll}\n",
       " Bought.Deposit & Did.not.Bought.Deposit & Total\\\\\n",
       " <int> & <int> & <int>\\\\\n",
       "\\hline\n",
       "\t 5289 & 39922 & 45211\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 1 × 3\n",
       "\n",
       "| Bought.Deposit &lt;int&gt; | Did.not.Bought.Deposit &lt;int&gt; | Total &lt;int&gt; |\n",
       "|---|---|---|\n",
       "| 5289 | 39922 | 45211 |\n",
       "\n"
      ],
      "text/plain": [
       "  Bought.Deposit Did.not.Bought.Deposit Total\n",
       "1 5289           39922                  45211"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "summarization <- data.frame(\"Bought Deposit\" = nrow(filter(bank_train, y == \"yes\")), \n",
    "                            \"Did not Bought Deposit\" = nrow(filter(bank_train, y == \"no\")),\n",
    "                            \"Total\" = nrow(bank_train))\n",
    "summarization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 600,
       "width": 900
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#bar chart of age and term deposit(predict variable)\n",
    "options(repr.plot.width = 15, repr.plot.height = 10) \n",
    "age_subscribe_plot <- \n",
    "     ggplot(bank_train, aes(y = age)) +\n",
    "     geom_bar(aes(fill = y), position = position_stack(reverse = TRUE)) +\n",
    "     labs(x = \"Number of Clients (Count)\", y = \"Age of Client\", fill = \"Has the client subscribed a term deposit?\") +\n",
    "     ggtitle(\"Number of Clients vs Age of Clients\") +\n",
    "     theme(legend.position = \"right\", text = element_text(size = 20))\n",
    "\n",
    "age_subscribe_plot\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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yUzZt6PjmQnsKLgAAIABJREFUmOjnNv76eiPjQ7+dzl8yCP3m+QsfTZ/a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qVy95t23uehtOy2/53/t98JXvcm/MCk1f4Koa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PA3X7BktO7tuVWG02upfSjJl8WucEQX+nV0dHR0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\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b2i5A4j1OF4Y0c6skVsMIE3JTiwVzjH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O2eece6113/VLLpuztHLZRS/mFZdg6kye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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 600,
       "width": 1020
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#scattor plot of age and balance\n",
    "options(repr.plot.width = 17, repr.plot.height = 10) \n",
    "age_balance_plot <- bank_train %>%\n",
    "    ggplot(aes(x = age, y =  balance)) + \n",
    "        geom_point(aes(colour = y)) +\n",
    "        labs(x = \"Age\", y = \"Credit Card Balance\", colour = \"Has the client subscribed a term deposit?\") +\n",
    "        ggtitle(\"Age vs Credit Card Balance\") +\n",
    "        theme(text = element_text(size=20))\n",
    "\n",
    "age_balance_plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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NcdBHfffXfYq664uDjsfxfU8g2Jekn+K2tKyYeaiS9t3759ONGULSe5+OjMy5Yt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\nxx13vPnmmwsXLiwvLw+P8fjjjz/jjDOijyFvuummgoKCv/71r4s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8bEvqk+aSr18hcAjCxcDL2b4lPM7dGmzhhqskOnz7wmtokQ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cIzM5w9Vgr6oBAPQf2b47rF78bb5P0+Mz2atF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\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2L3BoBXt25dnZbp1GhpEDP9/tdaywrn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\nBHDxMQWbO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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 600,
       "width": 1020
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#scattor plot of age and previous\n",
    "options(repr.plot.width = 17, repr.plot.height = 10) \n",
    "age_previous_plot <- bank_train %>%\n",
    "    ggplot(aes(x = age, y =  previous)) + \n",
    "        geom_point(aes(colour = y)) +\n",
    "        labs(x = \"Age\", y = \"Number of Contacts Performed Previously\", colour = \"Has the client subscribed a term deposit?\") + \n",
    "        ggtitle(\"Age vs Number of Contacts Performed Previously\") +\n",
    "        theme(text = element_text(size=20))\n",
    "\n",
    "age_previous_plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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zZFrv7UJO6LEDpd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\nAPa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3e+hGeMV4vJxYqi3/bhknqMdm5d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\nZ+o/iQxHqh2Tb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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 600,
       "width": 1020
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#scattor plot of balance and previous\n",
    "options(repr.plot.width = 17, repr.plot.height = 10) \n",
    "age_previous_plot <- bank_train %>%\n",
    "    ggplot(aes(x = previous, y =  balance)) + \n",
    "        geom_point(aes(colour = y)) +\n",
    "        labs(x = \"Number of Contacts Performed Previously\", y = \"Credit Card Balance\", colour = \"Has the client subscribed a term deposit?\") + \n",
    "        ggtitle(\"Number of Contacts Performed Previously vs Credit Card Balance\") +\n",
    "        theme(text = element_text(size=20))\n",
    "\n",
    "age_previous_plot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Methods:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "K- nearest neighbours: To classify an example xitilda:\n",
    "1. Find the ‘k’ training examples xi that are “nearest” to  xitilda.\n",
    "2. Classify using the most common label of “nearest” training examples.\n",
    "\n",
    "Using L2 norm(\"euclidean norm\") : ||r2||_2 = sqrt(r1^2 + r2^2)\n",
    "k = split data into training and validation data, then use validation error to choose k. \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "bank.csv\n",
    "The predicted label( variable y) is if or not the client will subscribe (yes/no) a term deposit. \n",
    "The features (variable x): 6 choosen from 16 variables"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "bank client data: <br>\n",
    "age (numeric); job : type of job (categorical);  loan: has personal loan? (categorical: 'no','yes','unknown'); balance (numeric)\n",
    "social and economic context attributes: <br>\n",
    "employment variation rate - quarterly indicator (numeric); consumer price index - monthly indicator (numeric) ; "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Result Visualization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p>By using a scatterplot, with the most weighted attribute variable on x-axis and the second most weighted attribute on y-axis, we are easiler to plot the location of each point <br>\n",
    "Each point in the plane is colored by their classification (yes or no), which would be assigned to it using the K-Nearest Neighbors algorithm.<br>\n",
    "The points with the same prediction result usually have shorter distance, since they are \"neighbours\". "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Expected Outcomes and Significance"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We expect to use the numerical methods to find what is the main decision factor that makes the clients deposit their money into the bank based on the comparison of the choosing factors.<br>\n",
    "\n",
    "Upon finding out what the main deciding factor is, we can review and enhance our marketing strategies to better target specific areas. \n",
    "\n",
    "In future, addressing the predictions of other marketing variables such as in the case of telemarketing where duration of calls is considered (which affects the probability of successful contacts highly) and amounts deposited into the bank. This will optimize on the strategic operations of the bank resulting in gains by the bank.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## References"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Chen, J. (2021, April 29). Term Deposit. Retrieved August 12, 2021, from https://www.investopedia.com/terms/t/termdeposit.asp\n",
    "\n",
    "Westpac. (n.d.). What's the difference between a term deposit and a savings account? Retrieved from https://www.westpac.com.au/personal-banking/bank-accounts/term-deposit/savings-vs-term-deposit/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "#########################################################################################################################"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A tibble: 60 × 7</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>neighbors</th><th scope=col>.metric</th><th scope=col>.estimator</th><th scope=col>mean</th><th scope=col>n</th><th scope=col>std_err</th><th scope=col>.config</th></tr>\n",
       "\t<tr><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;chr&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>1</td><td>accuracy</td><td>binary</td><td>0.8274501</td><td>5</td><td>0.0011610168</td><td>Model01</td></tr>\n",
       "\t<tr><td>1</td><td>roc_auc </td><td>binary</td><td>0.5942766</td><td>5</td><td>0.0033897018</td><td>Model01</td></tr>\n",
       "\t<tr><td>2</td><td>accuracy</td><td>binary</td><td>0.8280694</td><td>5</td><td>0.0009150839</td><td>Model02</td></tr>\n",
       "\t<tr><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td></tr>\n",
       "\t<tr><td>29</td><td>roc_auc </td><td>binary</td><td>0.6719121</td><td>5</td><td>0.0047386336</td><td>Model29</td></tr>\n",
       "\t<tr><td>30</td><td>accuracy</td><td>binary</td><td>0.8823027</td><td>5</td><td>0.0002404436</td><td>Model30</td></tr>\n",
       "\t<tr><td>30</td><td>roc_auc </td><td>binary</td><td>0.6730115</td><td>5</td><td>0.0048591182</td><td>Model30</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A tibble: 60 × 7\n",
       "\\begin{tabular}{lllllll}\n",
       " neighbors & .metric & .estimator & mean & n & std\\_err & .config\\\\\n",
       " <dbl> & <chr> & <chr> & <dbl> & <int> & <dbl> & <chr>\\\\\n",
       "\\hline\n",
       "\t 1 & accuracy & binary & 0.8274501 & 5 & 0.0011610168 & Model01\\\\\n",
       "\t 1 & roc\\_auc  & binary & 0.5942766 & 5 & 0.0033897018 & Model01\\\\\n",
       "\t 2 & accuracy & binary & 0.8280694 & 5 & 0.0009150839 & Model02\\\\\n",
       "\t ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮\\\\\n",
       "\t 29 & roc\\_auc  & binary & 0.6719121 & 5 & 0.0047386336 & Model29\\\\\n",
       "\t 30 & accuracy & binary & 0.8823027 & 5 & 0.0002404436 & Model30\\\\\n",
       "\t 30 & roc\\_auc  & binary & 0.6730115 & 5 & 0.0048591182 & Model30\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A tibble: 60 × 7\n",
       "\n",
       "| neighbors &lt;dbl&gt; | .metric &lt;chr&gt; | .estimator &lt;chr&gt; | mean &lt;dbl&gt; | n &lt;int&gt; | std_err &lt;dbl&gt; | .config &lt;chr&gt; |\n",
       "|---|---|---|---|---|---|---|\n",
       "| 1 | accuracy | binary | 0.8274501 | 5 | 0.0011610168 | Model01 |\n",
       "| 1 | roc_auc  | binary | 0.5942766 | 5 | 0.0033897018 | Model01 |\n",
       "| 2 | accuracy | binary | 0.8280694 | 5 | 0.0009150839 | Model02 |\n",
       "| ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ |\n",
       "| 29 | roc_auc  | binary | 0.6719121 | 5 | 0.0047386336 | Model29 |\n",
       "| 30 | accuracy | binary | 0.8823027 | 5 | 0.0002404436 | Model30 |\n",
       "| 30 | roc_auc  | binary | 0.6730115 | 5 | 0.0048591182 | Model30 |\n",
       "\n"
      ],
      "text/plain": [
       "   neighbors .metric  .estimator mean      n std_err      .config\n",
       "1  1         accuracy binary     0.8274501 5 0.0011610168 Model01\n",
       "2  1         roc_auc  binary     0.5942766 5 0.0033897018 Model01\n",
       "3  2         accuracy binary     0.8280694 5 0.0009150839 Model02\n",
       "⋮  ⋮         ⋮        ⋮          ⋮         ⋮ ⋮            ⋮      \n",
       "58 29        roc_auc  binary     0.6719121 5 0.0047386336 Model29\n",
       "59 30        accuracy binary     0.8823027 5 0.0002404436 Model30\n",
       "60 30        roc_auc  binary     0.6730115 5 0.0048591182 Model30"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#setting recipt\n",
    "knn_recipe <- recipe(y ~ age + job + marital+ education+balance+housing+loan, data = bank_train) %>%\n",
    "   step_scale(age, balance) %>%   # we dont need to scale factors\n",
    "   step_center(age, balance)\n",
    "\n",
    "gridvals<- tibble(neighbors = seq(from = 1,to = 30, by = 1))\n",
    "\n",
    "knn_tune <- nearest_neighbor(weight_func = \"rectangular\", neighbors = tune()) %>%\n",
    "      set_engine(\"kknn\") %>%\n",
    "      set_mode(\"classification\")\n",
    "\n",
    "bank_vfold <- vfold_cv(bank_train, v = 5, strata = y)\n",
    "\n",
    "knn_results <- workflow() %>%\n",
    "      add_recipe(knn_recipe) %>%\n",
    "      add_model(knn_tune) %>%\n",
    "      tune_grid(resamples = bank_vfold, grid = gridvals) %>%\n",
    "      collect_metrics() \n",
    "\n",
    "knn_results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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M9dfPv8jD3v9KC/eMmbP7Y23IHwJ8IPLBnCX7gmwv+F4x9+88vTfa2/OfoKL91u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\nRK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 600,
       "width": 1020
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "accuracies <- knn_results %>% \n",
    "      filter(.metric == \"accuracy\")\n",
    "accuracy_versus_k <- ggplot(accuracies, aes(x = neighbors, y = mean))+\n",
    "      geom_point() +\n",
    "      geom_line() +\n",
    "      labs(x = \"Neighbors\", y = \"Accuracy Estimate\") +\n",
    "      scale_x_continuous(breaks = seq(0, 14, by = 1)) +  \n",
    "      scale_y_continuous(limits = c(0.4, 1.0)) \n",
    "\n",
    "accuracy_versus_k"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A tibble: 1 × 7</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>neighbors</th><th scope=col>.metric</th><th scope=col>.estimator</th><th scope=col>mean</th><th scope=col>n</th><th scope=col>std_err</th><th scope=col>.config</th></tr>\n",
       "\t<tr><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;chr&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>30</td><td>accuracy</td><td>binary</td><td>0.8823027</td><td>5</td><td>0.0002404436</td><td>Model30</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A tibble: 1 × 7\n",
       "\\begin{tabular}{lllllll}\n",
       " neighbors & .metric & .estimator & mean & n & std\\_err & .config\\\\\n",
       " <dbl> & <chr> & <chr> & <dbl> & <int> & <dbl> & <chr>\\\\\n",
       "\\hline\n",
       "\t 30 & accuracy & binary & 0.8823027 & 5 & 0.0002404436 & Model30\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A tibble: 1 × 7\n",
       "\n",
       "| neighbors &lt;dbl&gt; | .metric &lt;chr&gt; | .estimator &lt;chr&gt; | mean &lt;dbl&gt; | n &lt;int&gt; | std_err &lt;dbl&gt; | .config &lt;chr&gt; |\n",
       "|---|---|---|---|---|---|---|\n",
       "| 30 | accuracy | binary | 0.8823027 | 5 | 0.0002404436 | Model30 |\n",
       "\n"
      ],
      "text/plain": [
       "  neighbors .metric  .estimator mean      n std_err      .config\n",
       "1 30        accuracy binary     0.8823027 5 0.0002404436 Model30"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "best_n <- knn_results %>%\n",
    "            arrange(desc(mean)) %>%\n",
    "            slice(1)\n",
    "\n",
    "best_n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "best_spec <- nearest_neighbor(weight_func = \"rectangular\", neighbors = 30) %>%\n",
    "      set_engine(\"kknn\") %>%\n",
    "      set_mode(\"classification\")\n",
    "\n",
    "best_fit <- workflow() %>%\n",
    "      add_recipe(knn_recipe) %>%\n",
    "      add_model(best_spec) %>%\n",
    "      fit(data = bank_train)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "bank_predictions <- predict(best_fit , bank_test) %>%\n",
    "      bind_cols(bank_test)\n",
    "\n",
    "pred_metrics <- bank_predictions %>%\n",
    "        metrics(truth = y, estimate = .pred_class)             \n",
    "\n",
    "pred_metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "ir"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "4.0.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}