Nothing
Creates classifier for binary outcomes using Adaptive Boosting (AdaBoost) algorithm on decision stumps with a fast C++ implementation. For a description of AdaBoost, see Freund and Schapire (1997) <doi:10.1006/jcss.1997.1504>. This type of classifier is nonlinear, but easy to interpret and visualize. Feature vectors may be a combination of continuous (numeric) and categorical (string, factor) elements. Methods for classifier assessment, predictions, and cross-validation also included.
Package details |
|
---|---|
Author | Jadon Wagstaff [aut, cre] |
Maintainer | Jadon Wagstaff <jadonw@gmail.com> |
License | MIT + file LICENSE |
Version | 0.1.2 |
URL | https://github.com/jadonwagstaff/sboost |
Package repository | View on CRAN |
Installation |
Install the latest version of this package by entering the following in R:
|
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.