partial.predict: Partial prediction for boosted models

In logicDT: Identifying Interactions Between Binary Predictors

Partial prediction for boosted models

Description

Alternative prediction function for logic.boosted models using up to n.iter boosting iterations. An array of predictions for every number of boosting iterations up to n.iter is returned.

Usage

partial.predict(model, X, Z = NULL, n.iter = 1, ...)

Arguments

model	Fitted logic.boosted model
X	Matrix or data frame of binary input data. This object should correspond to the binary matrix for fitting the model.
Z	Optional quantitative covariables supplied as a matrix or data frame. Only used (and required) if the model was fitted using them.
n.iter	Maximum number of boosting iterations for prediction
...	Parameters supplied to predict.logicDT

Details

The main purpose of this function is to retrieve the optimal number of boosting iterations (early stopping) using a validation data set and to restrict future predictions on this number of iterations.

Value

An array of dimension (N, n.iter) containing the partial predictions

logicDT documentation built on Sept. 23, 2024, 5:11 p.m.