Graphics for R

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https://cran.r-project.org/web/views/Graphics.html CRAN Task View: Graphic Displays & Dynamic Graphics & Graphic Devices & Visualization Maintainer: Nicholas Lewin-Koh Contact: nikko at hailmail.net Version: 2015-01-07 URL: https://CRAN.R-proj…

如何在R语言中使用Logistic回归模型

在日常学习或工作中经常会使用线性回归模型对某一事物进行预测,例如预测房价.身高.GDP.学生成绩等,发现这些被预测的变量都属于连续型变量.然而有些情况下,被预测变量可能是二元变量,即成功或失败.流失或不流失.涨或跌等,对于这类问题,线性回归将束手无策.这个时候就需要另一种回归方法进行预测,即Logistic回归. 在实际应用中,Logistic模型主要有三大用途: 1)寻找危险因素,找到某些影响因变量的"坏因素",一般可以通过优势比发现危险因素: 2)用于预测,可以预测某种情况发生的概…

More 3D Graphics (rgl) for Classification with Local Logistic Regression and Kernel Density Estimates (from The Elements of Statistical Learning)（转）

This post builds on a previous post, but can be read and understood independently. As part of my course on statistical learning, we created 3D graphics to foster a more intuitive understanding of the various methods that are used to relax the assumpt…

Some 3D Graphics (rgl) for Classification with Splines and Logistic Regression (from The Elements of Statistical Learning)（转）

This semester I'm teaching from Hastie, Tibshirani, and Friedman's book, The Elements of Statistical Learning, 2nd Edition. The authors provide aMixture Simulation data set that has two continuous predictors and a binary outcome. This data is used to…

【Graphics for R】的更多相关文章

Graphics for R

如何在R语言中使用Logistic回归模型

More 3D Graphics (rgl) for Classification with Local Logistic Regression and Kernel Density Estimates (from The Elements of Statistical Learning)（转）

Some 3D Graphics (rgl) for Classification with Splines and Logistic Regression (from The Elements of Statistical Learning)（转）

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