INTERNAL FUNCTION TO EVALUATE IMPORTANCE OF PREDICTOR COMBINATIONS.
Prepares a data frame with responses, weights, censoring indicators, and evaluated predicted values for each tree in a fitted logic regression model.
Called by predict.logreg2, not intended to be used independently.
frame.logreg2(fit, msz, ntr, newbin, newresp, newsep, newcens, newweight)A data.frame containing the response, weights, censoring indicators (if applicable), separate predictors, and evaluated predicted values for each tree.
An object of class "logreg" fit to the training data
Maximum number of leaves on a tree (optional)
Number of trees in the fit (optional)
Binary matrix of predictors for new/out-of-sample data
Vector of response values for new data
Matrix of separate predictors for new data
Vector of censoring indicators for new data (for survival models)
Optional vector of observation weights
This function constructs a data frame for evaluating predicted values from logic regression trees. It supports in-bag and out-of-sample data, handles optional censoring indicators, separate predictors, and observation weights. The resulting data frame contains columns for:
Response variable
Observation weights
Censoring indicators (for survival models)
Separate predictors (if applicable)
Predicted values from each tree in the model