This project showcases a fundamental machine learning technique known as linear regression, implemented using the Gradient Descent algorithm. The goal is to understand the relationship between dependent and independent variables in a dataset and use this relationship to make predictions. What is Linear ...
mlr: Machine Learning in R . Contribute to linearregression/mlr development by creating an account on GitHub.
当采用L1正则化时,则变成了LassoRegresion;当采用L2正则化时,则变成了Ridge Regression;线性回归未采用正则化手段。通常来说,在训练模型时是建议采用正则化手段的,特别是在训练数据的量特别少的时候,若不采用正则化手段,过拟合现象会非常严重。L2正则化相比L1而言会更容易收敛(迭代次数少),但L1可以解决训练数据量...
b.矩阵不满秩时(梯度下降): 梯度下降算法是一种求局部最优解的方法,对于F(x),在a点的梯度是F(x)增长最快的方向,那么它的相反方向则是该点下降最快的方向,具体参考wikipedia。 原理:将函数比作一座山,我们站在某个山坡上,往四周看,从哪个方向向下走一小步,能够下降的最快; 注意:当变量之间大小相差很大时,...
2.Linear regression with one variable 下一步,我们尝试用Octave绘图。 根据指导文件的提示,我们在plotData.m文件中写上: plot(x,y,'rx','MarkerSize',10);%Plot the dataylabel('Profit in $10,000s');%Set the y-axis labelxlabel('Population of City in 10,000s');%Set the x-axis label ...
通过看其他人在kaggle上分享的notebook以及自己的一些理解,记录一下Linear Regression的学习过程,也算是完成作业中的report.pdf。 二、Linear Regression(预测PM2.5) 1、准备工作 (1)作业要求(如图一所示) 图一 (2)train.csv、test.csv 链接:https://pan.baidu.com/s/1ZeOASD7SdyMUYwjo0uDaqA ...
One Variable Linear Regression Supervised learning, unsupervised learning, parameter learning and model and cost functions. Introduction to Machine Learning: Supervised and Unsupervised Learning I would like to give full credits to the respective authors as these are my personal python notebooks taken ...
%% Machine Learning Online Class - Exercise 1: Linear Regression% Instructions% ---%% This file contains code that helps you get started on the% linear exercise. You will need to complete the following functions% in this exericse:%% warmUpExercise.m% plotData.m 绘制房屋面积和房屋价格的点状...
源码:https://github.com/cheesezhe/Coursera-Machine-Learning-Exercise/tree/master/ex5 Introduction: In this exercise, you will implement regularized linear regression and use it to study models with different bias-variance properties. 1. Regularized Linear Regression ...
Confidence in model, hypothesis testing, p-values, feature selection, train/test splitContents Introduction Libraries Example: Advertising Data Questions About the Advertising Data Simple Linear Regression Estimating ("Learning") Model Coefficients Interpreting Model Coefficients Using the Model for Prediction...