demo8.py

import numpy as np
from sklearn import linear_model, datasets

'''
diabetes = datasets.load_diabetes()
print(type(diabetes))
print("X, features shape is:", diabetes.data.shape)
print("Y, labels shape is:", diabetes.target.shape, "\n")

dataForTest = -50
data_train = diabetes.data[:dataForTest]
target_train = diabetes.target[:dataForTest]
print("data trained shape:", data_train.shape)
print("target trained shape:", target_train.shape)

data_test = diabetes.data[dataForTest:]
target_test = diabetes.target[dataForTest:]
print("data test shape:", data_test.shape)
print("target test shape:", target_test.shape)

regression1 = linear_model.LinearRegression()
regression1.fit(data_train, target_train)

print(regression1, "\n")  # put debug here

print("score:", regression1.score(data_test, target_test))

for i in range(dataForTest, 0):
    # print(data_test[i].shape, data_test[i])
    dataArray = np.array(data_test[i].reshape(1, -1))
    # print(dataArray.shape, dataArray)
    print(f"predict = {regression1.predict(dataArray)[0]:.1f}/ actual = {target_test[i]}")
'''

diabetes = datasets.load_diabetes()
print(type(diabetes))
print("X, features shape is:", diabetes.data.shape)
print("Y, labels shape is:", diabetes.target.shape, "\n")

dataForTest = -50
data_train = diabetes.data[:dataForTest]
target_train = diabetes.target[:dataForTest]
print("data trained shape:", data_train.shape)
print("target trained shape:", target_train.shape)

data_test = diabetes.data[dataForTest:]
target_test = diabetes.target[dataForTest:]
print("data test shape:", data_test.shape)
print("target test shape:", target_test.shape)

regression1 = linear_model.LinearRegression()
regression1.fit(data_train, target_train)

print(regression1, "\n")  # put debug here

print("score:", regression1.score(data_test, target_test))
predicts = regression1.predict(data_test)
print(f"predicts shape = {predicts.shape}")

for i in range(len(predicts)):
    print(f"predict = {predicts[i]:.1f}/ actual = {target_test[-50+ i]},")


# for i in range(dataForTest, 0):
    # print(data_test[i].shape, data_test[i])
    # dataArray = np.array(data_test[i].reshape(1, -1))
    # print(dataArray.shape, dataArray)
    # print(f"predict = {regression1.predict(dataArray)[0]:.1f}/ actual = {target_test[i]}")