[机器学习]机器学习笔记整理13

1. 简单线性回归模型举例：

汽车卖家做电视广告数量与卖出的汽车数量：

1.1 如何练处适合简单线性回归模型的最佳回归线？

1.2 计算

预测：

假设有一周广告数量为6，预测的汽车销售量是多少？

代码实现

x_given = 6Y_hat = 5*6 + 10 = 401.3 Python实现：import numpy as npdef fitSLR(x, y): n = len(x) dinominator = 0 numerator = 0 for i in range(0, n): numerator += (x[i] - np.mean(x))*(y[i] - np.mean(y)) dinominator += (x[i] - np.mean(x))**2 b1 = numerator/float(dinominator) b0 = np.mean(y)/float(np.mean(x)) return b0, b1def predict(x, b0, b1): return b0 + x*b1x = [1, 3, 2, 1, 3]y = [14, 24, 18, 17, 27] b0, b1 = fitSLR(x, y)print 'intercept:', b0, ' slope:', b1x_test = 6y_test = predict(6, b0, b1)print 'y_test:', y_test