persistence.prep

 an object of class <code>logforest</code>.


 a numeric value representing the number of predictors in the original data used to construct the logic forest model.


preds

 a charachter string for the variable or interaction term to be considered for matching


Internal function called by <code><a rd-options="" href="/link/persistence.plot?package=LogicForest&version=2.1.0" data-mini-rdoc="LogicForest::persistence.plot">persistence.plot</a></code>.  Not intended to be used independt of this function.


internal

Two classification ensemble methods based on logic regression models.  LogForest uses a bagging approach to construct an ensemble of logic regression models.  LBoost uses a combination of boosting and cross-validation to construct an ensemble of logic regression models.  Both methods are used for classification of binary responses based on binary predictors and for identification of important variables and variable interactions predictive of a binary outcome.

persistence.prep: Internal Logic forest Functions

Description

Usage

Arguments