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.
This package is very useful because it summarizes several common machine learning algorithms in one package. Moreover, these algorithms can be executed in parallel on our own computer, as it is very fast. The package includes...
