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Book Overview & Buying
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Table Of Contents
Machine Learning For Dummies
By :
https://web.stanford.edu/~hastie/glmnet/glmnet_alpha.html
The “Guessing the Right Features” section of Chapter 15 discusses regularization as an effective, fast, and easy solution to use when you have many features and want to reduce the variance of the estimates due to multicollinearity between your predictors. One form of regularization discussed in that chapter is Lasso, which is one of the forms of support you get from glmnet (with the other being elastic-net). This package fits the linear, logistic and multinomial, Poisson, and Cox regression models. You can also use this package to perform prediction, plotting, and K-fold cross-validation. Professor Rob Tibshirani, the creator of the L1 (also known as Lasso) regularization also helped develop this package. The easiest way to get this package is by downloading it from https://cran.r-project.org/web/packages/glmnet/index.html. In addition, Gensim provides multiprocessing and out-of-core capabilities, allowing...
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