Day_2 簡單線性迴歸模型
阿新 • • 發佈:2018-12-04
第一步:資料預處理 In [2]: import pandas as pd import numpy as np import matplotlib.pyplot as plt dataset = pd.read_csv('studentscores.csv') X = dataset.iloc[:, : 1].values Y = dataset.iloc[:, 1].values from sklearn.model_selection import train_test_split X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size = 1/4, random_state = 0) 第二步:訓練集使用簡單線性迴歸模型來訓練 In [3]: from sklearn.linear_model import LinearRegression regressor = LinearRegression() regressor = regressor.fit(X_train, Y_train) 第三步:預測結果 In [4]: Y_pred = regressor.predict(X_test) 第四步:視覺化 訓練集結果視覺化 In [5]: plt.scatter(X_train, Y_train, color = 'red') plt.plot(X_train, regressor.predict(X_train),color = 'blue') plt.show()
plt.scatter(X_test, Y_test, color = 'red')
plt.plot(X_test, regressor.predict(X_test),color = 'green')
plt.show()