机器学习3-简单线性回归

需求：

现在要根据学生的学习时间来预测学习成绩，给出现有数据，用来训练模型并预测新数据。

分析：

使用线性回归模型。

代码：

import pandas as pd
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression

dataset = pd.read_csv('studentscores.csv')
X = dataset.iloc[ : , :1 ].values
Y = dataset.iloc[ : , 1 ].values

X_train, X_test, Y_train, Y_test = train_test_split( X, Y, test_size = 1/4, random_state = 0)


regressor = LinearRegression()
regressor = regressor.fit(X_train, Y_train)

Y_pred = regressor.predict(X_test)


plt.scatter(X_train , Y_train, color = 'red')
plt.plot(X_train , regressor.predict(X_train), color ='blue')

plt.scatter(X_test , Y_test, color = 'blue'