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...
In Excel, Linear Regression is a statistical tool and a built-in function used to find the best-fitting straight line that describes the linear relationship between two or more variables. It is commonly employed for predictive modeling and analyzing the relationship between a dependent variable and ...
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] *...
§ 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...
graph. Linear regression should only be performed if linear relationships exist between the dependent variable and each of the input variables. Excel X-Y scatterplots of the two independent variables versus the dependent variable are shown as follows. The relationships in both cases appear to be ...
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...
使用最小二乘法拟合的普通线性回归是数据建模的基本方法。 令最小二乘项的偏导为0(为0时RSS项最小),求Beta估计值,得到最小二乘的向量形式。 最小二乘其实就是找出一组参数beta使得训练数据到拟合出的数据的欧式距离最小。如下图所示,使所有红点(训练数据)到平面的距离之和最小。
Linear Regression analysis in Excel. Analytics in Excel includes regression analysis, Goal seek and What-if analysis 评分:4.6,满分 5 分4.6(1124 个评分) 104,311 个学生 创建者Start-Tech Academy 上次更新时间:2/2025 英语 英语[自动], 韩语 [自动] ...
文档介绍:Statistics for Managers Using Microsoft® Excel 5th EditionChapter 14Introduction to Multiple RegressionChap 14-1Learning ObjectivesIn this chapter, you learn:How to develop a multiple regression modelHow to interpret the regression coefficientsHow to determine which independent variables to ...
You can use linear regression to compare two or more variables, such as a specific stock with a benchmark, to determine their dependence, which can help make certain investment decisions. A linear regression model can be created in Excel to make the process simpler....