Explore Classification Models in High Dimensions R package classifly version 0.4.3 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 non-linear. This package implements methods for understanding the division of space between the groups. Software Imports: class, plyr, stats Suggests: e1071, MASS, rpart Dianne Cook <visnut@gmail.com> Comprehensive R Archive Network (CRAN) Hadley Wickham [aut], Dianne Cook [cre] MIT + file LICENSE (https://CRAN.R-project.org/package=classifly/LICENSE) 2026-03-15 application/tgz https://CRAN.R-project.org/package=classifly doi:10.32614/CRAN.package.classifly