Machine learning （7-Regularization）

1、The Problem of Over-fitting

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2、Cost Function

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3、Regularized Linear Regression

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4、Regularized Logistic Regression

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import numpy as np
def costReg(theta, X, y, learningRate):
 theta = np.matrix(theta)
 X = np.matrix(X)
 y = np.matrix(y)
 first = np.multiply(-y, np.log(sigmoid(X*theta.T)))
 second = np.multiply((1 - y), np.log(1 - sigmoid(X*theta.T)))
 reg = (learningRate / (2 * len(X))* np.sum(np.power(theta[:,1:the
ta.shape[1]],2))
 return np.sum(first - second) / (len(X)) + reg