Machine Learning with R Quick Start Guide by Iván Pastor Sanz

Author:Iván Pastor Sanz
Language: eng
Format: epub
Tags: COM004000 - COMPUTERS / Intelligence (AI) and Semantics, COM037000 - COMPUTERS / Machine Theory, COM018000 - COMPUTERS / Data Processing
Publisher: Packt Publishing
Published: 2019-03-29T10:06:12+00:00

Regularized methods

There are three common approaches to using regularized methods:

Lasso

Ridge

Elastic net

In this section, we will see how these methods can be implemented in R. For these models, we will use the h2o package. This provides a predictive analysis platform to be used in machine learning that is open source, based on in-memory parameters, and distributed, fast, and scalable. It helps in creating models that are built on big data and is most suitable for enterprise applications as it enhances production quality.

For more information on the h2o package, please visit its documentation at https://cran.r-project.org/web/packages/h2o/index.html.

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