In classification problems a monotone relation between some predictors and the classes may be assumed. In this package 'isoboost' we propose new boosting algorithms, based on LogitBoost, that incorporate this isotonicity information, yielding more accurate and easily interpretable rules.
|Author||David Conde [aut, cre], Miguel A. Fernandez [aut], Cristina Rueda [aut], Bonifacio Salvador [aut]|
|Maintainer||David Conde <firstname.lastname@example.org>|
|License||GPL-2 | GPL-3|
|Package repository||View on CRAN|
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