logicDT: Identifying Interactions Between Binary Predictors
A global statistical learning method
which tries to find the best set of predictors and interactions
between predictors for modeling binary or quantitative response data.
Several search algorithms and ensembling techniques are implemented
allowing for finetuning the method to the specific problem.
Interactions with single quantitative covariables can be properly
taken into account by also splitting after those or by fitting
local four parameter logistic models.
||graphics, stats, utils
||Michael Lau [aut,
||Michael Lau <michael.lau at hhu.de>
||MIT + file LICENSE
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