需要帮助了解python中的矩阵函数乘法

2024-05-20 • 问答

我正在尝试使用Python从Andrew Ng机器学习课程中找到优化的theta值以最小化成本函数。我的程序中的theta值不正确。我在这里看不懂什么？我正在尝试在这里学习...抱歉菜鸟问题

#Shapes of numpy arrays
#popx=(97,1)
#popxx=(97,2)#x in function
#profy=(97,1)#y in function

def gradientDescent(x,y,iterations=1500,alpha=0.01,theta=np.zeros(2).reshape(1,2)):
        cost=np.zeros(iterations)
        theta_Hist=[]
        m=len(profy)
        for i in range(iterations):
            print("Before Loop\n",theta)
            t=(alpha/m)*np.dot(popx.T,(np.dot(x,theta.T)-y))
            print(np.dot(popx.T,theta.T)-y)))
            theta=theta-t
            theta_Hist.append(theta)
            print("after\n",theta)
            cost[i]=computeCost(x,theta)
    gradientDescent(popxx,profy)

theta的值应为-3.24140214，1.1272942

import numpy as np def computeCost(X,y,theta): m = len(y) predictions = np.dot(X,theta) squared_error = (predictions-y)**2 cost = np.sum(squared_error)/(2*m) return cost def gradientDescent(x,theta,iterations=1500,alpha=0.01): cost_Hist=[] theta_Hist=[] n=len(y) for i in range(iterations): prediction = np.dot(x,theta) error = prediction - y grad = np.dot(x.T,error) theta = theta - (alpha/n)*grad co = computeCost(x,theta) theta_Hist.append(theta) cost_Hist.append(co) return theta init_thetas = np.zeros(shape=(2,1)) thetas = gradientDescent(X,init_thetas)

需要帮助了解python中的矩阵函数乘法

gush5051 回答：需要帮助了解python中的矩阵函数乘法

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