扣丁学堂Python培训简述Python实现的线性回归算法示例

本篇文章扣丁学堂Python培训小编给小伙伴们实例分享一下Python实现的线性回归算法，涉及Python使用最小二乘法、梯度下降算法实现线性回归相关算法操作与使用技巧，需要的朋友就随小编一起来学习了解一下吧。 代码： #encoding:utf-8 """ Project： Using Python to Implement LineRegression Algorithm """ import numpy as np import pandas as pd from numpy.linalg import inv from numpy import dot from sklearn.model_selection import train_test_split import matplotlib.pyplot as plt from sklearn import linear_model # 最小二乘法 def lms(x_train,y_train,x_test): theta_n = dot(dot(inv(dot(x_train.T, x_train)), x_train.T), y_train) # theta = (X'X)^(-1)X'Y #print(theta_n) y_pre = dot(x_test,theta_n) mse = np.average((y_test-y_pre)**2) #print(len(y_pre)) #print(mse) return theta_n,y_pre,mse #梯度下降算法 def train(x_train, y_train, num, alpha,m, n): beta = np.ones(n) for i in range(num): h = np.dot(x_train, beta) # 计算预测值 error = h - y_train.T # 计算预测值与训练集的差值 delt = 2*alpha * np.dot(error, x_train)/m # 计算参数的梯度变化值 beta = beta - delt #print('error', error) return beta if __name__ == "__main__": iris = pd.read_csv('iris.csv') iris['Bias'] = float(1) x = iris[['Sepal.Width', 'Petal.Length', 'Petal.Width', 'Bias']] y = iris['Sepal.Length'] x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.2, random_state=5) t = np.arange(len(x_test)) m, n = np.shape(x_train) # Leastsquare theta_n, y_pre, mse = lms(x_train, y_train, x_test) # plt.plot(t, y_test, label='Test') # plt.plot(t, y_pre, label='Predict') # plt.show() # GradientDescent beta = train(x_train, y_train, 1000, 0.001, m, n) y_predict = np.dot(x_test, beta.T) # plt.plot(t, y_predict) # plt.plot(t, y_test) # plt.show() # sklearn regr = linear_model.LinearRegression() regr.fit(x_train, y_train) y_p = regr.predict(x_test) print(regr.coef_,theta_n,beta) l1,=plt.plot(t, y_predict) l2,=plt.plot(t, y_p) l3,=plt.plot(t, y_pre) l4,=plt.plot(t, y_test) plt.legend(handles=[l1, l2,l3,l4 ], labels=['GradientDescent', 'sklearn','Leastsquare','True'], loc='best') plt.show() 想要了解更多关于Python和人工智能方面内容的小伙伴，请关注扣丁学堂Python培训官网、微信等平台，扣丁学堂IT职业在线学习教育平台为您提供权威的Python开发环境搭建视频，Python培训后的前景无限，行业薪资和未来的发展会越来越好的，扣丁学堂老师精心推出的Python视频教程定能让你快速掌握Python从入门到精通开发实战技能。扣丁学堂Python技术交流群：279521237。