predict.logicDT: Prediction for logicDT models

In logicDT: Identifying Interactions Between Binary Predictors

Prediction for logicDT models

Description

Supply new input data for predicting the outcome with a fitted logicDT model.

Usage

## S3 method for class 'logic.bagged'
predict(object, X, Z = NULL, type = "prob", ...)

## S3 method for class 'logic.boosted'
predict(object, X, Z = NULL, type = "prob", ...)

## S3 method for class 'logicDT'
predict(
  object,
  X,
  Z = NULL,
  type = "prob",
  ensemble = FALSE,
  leaves = "4pl",
  ...
)

## S3 method for class 'geneticLogicPET'
predict(
  object,
  X,
  Z = NULL,
  models = "best",
  n_models = 10,
  ensemble = NULL,
  leaves = "4pl",
  ...
)

Arguments

object	Fitted logicDT model. Usually a product of a call to logicDT.
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.
type	Prediction type. This can either be "prob" for probability estimates or "class" for classification in binary responses. Ignored for regression.
...	Parameters supplied to predict.logicDT
ensemble	If the model was fitted using the inner validation approach, shall the prediction be constructed using the final validated ensemble (TRUE) or using the single final tree (FALSE)?
leaves	If four parameter logistic models were fitted for each leaf, shall they be used for the prediction ("4pl") or shall the constant leaf means be used ("constant")?
models	Which models of logicDT model fitted with genetic programming shall be used for prediction? "best" leads to the single best model in the final generation, "all" uses the average over the final generation and "n_models" uses the n_models best models.
n_models	How many models shall be used if models = "n_models" and genetic programming was employed?

Value

A numeric vector of predictions. For binary outcomes, this is a vector with estimates for P(Y=1 \mid X = x).

logicDT documentation built on Jan. 14, 2023, 5:06 p.m.