J_history=np.zeros((num_iters,1))foriterinrange(num_iters):# 对J求导,得到 alpha/m*(WX-Y)*x(i),(3,m)*(m,1)X(m,3)*(3,1)=(m,1)theta=theta-(alpha/m)*(X.T.dot(X.dot(theta)-y))J_history[iter]=computeCost(X,y,theta)returnJ_history,theta iterations=10000#迭代次数 alph...
§ 2. 多变量线性回归 Linear Regression with Multiple Variables 1 多特征值(多变量) Multiple Features(Variables) 首先,举例说明了多特征值(多变量)的情况。在下图的例子中,x1,x2,x3,x4x1,x2,x3,x4都是输入的变量,因为变量个数大于一,所以也称为多变量的情况。 于是引出多变量线性回归的一般假设形式: 2...
import math; def sum_of_gradient(x, y, thetas): """计算梯度向量,参数分别是x和y轴点坐标数据以及方程参数""" m = len(x); grad0 = 1.0 / m * sum([(thetas[0] + thetas[1] * x[i] - y[i]) for i in range(m)]) grad1 = 1.0 / m * sum([(thetas[0] + thetas[1] *...
J_history=np.zeros((num_iters,1)) foriterinrange(num_iters): #对J求导,得到 alpha/m * (WX - Y)*x(i), (3,m)*(m,1) X (m,3)*(3,1) = (m,1) theta=theta-(alpha/m)*(X.T.dot(X.dot(theta)-y)) J_history[iter]=computeCost(X, y, theta) returnJ_history,theta iterati...
4 多变量线性回归(Linear Regression with Multiple Variables)4.1 多特征(Multiple Features)4.2 多变量梯度下降(Gradient Descent for Multiple Variables)4.3 梯度下降实践1-特征值缩放(Gradient Descent in Practice I - Feature Scaling)4.4 梯度下降实践2-学习速率(Gradient Descent in Practice II - Learning Rate...
2. Can I perform a linear regression analysis in Excel with multiple independent variables? Yes, You can perform linear regression analysis with multiple independent variables. This is particularly useful when analyzing complex relationships between multiple factors. ...
[Section 2] Gradient Descent for Multiple Variables [Section 3] Gradient Descent in Practice I - Feature Scaling [Section 4] Gradient Descent in Practice II - Learning Rate [Section 5] Features and Polynomial Regression [Section 6] Normal Equation ...
MULTIPLE LINEAR REGRESSION ANALYSIS USING MICROSOFT EXCEL by Michael L. Orlov Chemistry Department, Oregon State University (1996) INTRODUCTION In modern science, regression analysis is a necessary part of virtually almost any data reduction process. Popular spreadsheet programs, such as Quattro Pro,...
Excel Multiple Linear Regression Step 5 – Run the Regression Analysis Below is the Regression dialogue box with all of the necessary information filled in. Many of the required regression assumptions concerning the Residuals have not yet been validated. Calculating and evaluating the Residuals will be...
The coefficients of the multiple regression model are estimated using sample dataEstimated (or predicted) value of YEstimated slope coefficientsMultiple regression equation with k independent variables:EstimatedinterceptIn this chapter we will always use Excel to obtain the regression slope coefficients and...