classifly: Explore classification models in high dimensions
Version 0.4

Given $p$-dimensional training data containing $d$ groups (the design space), a classification algorithm (classifier) predicts which group new data belongs to. Generally the input to these algorithms is high dimensional, and the boundaries between groups will be high dimensional and perhaps curvilinear or multi-faceted. This package implements methods for understanding the division of space between the groups.

Getting started

Package details

AuthorHadley Wickham <[email protected]>
Date of publication2014-04-23 19:51:22
MaintainerHadley Wickham <[email protected]>
LicenseMIT + file LICENSE
Package repositoryView on CRAN
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classifly documentation built on May 29, 2017, 6:18 p.m.