LBoost.fit

The LBoost model for data with a binary response with error following the underlying logical relationship 
L=(X4 and X5) or (X9 and X10)
The LBoost model used 5-fold cross validation and includes 100 logic regression trees. Predictor importance and two measures of interaction (prime implicant) importance were also run as part of the model.

datasets

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.

LBoost.fit: Example of a LBoost Model

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Examples