Machine learning (7-Regularization)
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1、The Problem of Over-fitting
2、Cost Function
3、Regularized Linear Regression
4、Regularized Logistic Regression
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
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