Learning Predictive Analytics with R: Get to grips with key data visualization and predictive analytic skills using R

✍ Scribed by Eric Mayor

Publisher: Packt Publishing
Year: 2015
Tongue: English
Leaves: 333
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

R is statistical software that is used for data analysis. There are two main types of learning from data: unsupervised learning, where the structure of data is extracted automatically; and supervised learning, where a labeled part of the data is used to learn the relationship or scores in a target attribute. As important information is often hidden in a lot of data, R helps to extract that information with its many standard and cutting-edge statistical functions. This book is packed with easy-to-follow guidelines that explain the workings of the many key data mining tools of R, which are used to discover knowledge from your data.

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Problems with linear regression -- Multicollinearity -- Outliers -- Feature selection -- Regularization -- Ridge regression -- Least absolute shrinkage and selection operator (lasso) -- Implementing regularization in R -- Polynomial regression -- Summary -- Chapter 4: Generalized Linear Models -- Cl