【吴恩达机器学习笔记】004 模型示例:单变量线性回归(Model Representation:Linear Regression with one variable) 一、示例 —— 预测住房价格 如上图所示,图中的数据集(X)表示房屋大小和价格存在的一个关系图。如果有一个人有一套1250平方尺的房子,那他卖多少钱合适? 二、分析 或许我们每个人心中... tcp三
(一)单变量线性回归 Linear Regression with One Variable (二)多变量线性回归 Linear Regression with Multiple Variables (三)逻辑回归 Logistic Regression (四)正则化与过拟合问题 Regularization/The Problem of Overfitting (五)神经网络的表示 Neural Networks:Representation (六)神经网络的学习 Neural Networks:Lear...
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] *...
defload_exdata(filename):data=[]withopen(filename,'r')asf:forlineinf.readlines():line=line.split(',')current=[int(item)foriteminline]#5.5277,9.1302data.append(current)returndata data=load_exdata('ex1data2.txt');data=np.array(data,np.int64)x=data[:,(0,1)].reshape((-1,2))y=dat...
2. Gradient descent for multiple variable 下面来看一下多变量下梯度下降算法的定义: Hypothesis : Parameters : 共n+1个参数 Cost Function : Gadient Descent : Repeat { simultaneously update for every } 原来单变量的梯度下降算法与现在对变量的梯度下降算法比较,最关键的就是一定要同时进行更新。
【Machine Learning】4 多变量线性回归(Linear Regression with Multiple Variables) 4.1 多维特征 4.2 多变量梯度下降 4.3 梯度下降实践1-特征缩放 4.4 梯度下降实践2-学习率 满足wolfe条件,充分下降且步长不能太小 这个比较简单,在数值优化中有详细介绍 4.5 特征和多项式回归... ...
一、Linear Regression 主要分为Linear Regression with One Variable & Linear Regression with Multiple Variables Linear Regression with One Variable 简单地说就是一个自变量一个因变量,且二者的关系近似可以用一条直线去拟合。 例如房价与面积的关系,就可以近似看成单变量线性回归问题 ...
Linear regression with multiple variables(多特征的线型回归)算法实例_梯度下降解法(Gradient DesentMulti)以及正规方程解法(Normal Equation),%第一列为sizeofHouse(feet^2),第二列为numberofbedroom,第三列为priceofHouse12104,3,39990021600,3,32990032400,3,3690004
Multiple regression differs from ANOVA, in which the predictors are represented as ''factors" with multiple discrete "levels." In this report, we focus on multiple regression to analyze data sets in which the response variable is continuous; other methods, such as logistic regression and ...
Linear regression and multiple regression are two types of regression analysis. Key Takeaways Regression analysis is a statistical method used in finance and investing. Linear regression (also called simple regression) contains only two variables: the independent variable and the dependent variable....