predictors {caret}R Documentation

List predictors used in the model

Description

This class uses a model fit to determine which predictors were used in the final model.

Usage

predictors(x, ...)

## S3 method for class 'train':
predictors(x,  ...)

## S3 method for class 'terms':
predictors(x,  ...)

## S3 method for class 'formula':
predictors(x,  ...)

## S3 method for class 'list':
predictors(x,  ...)

## S3 method for class 'mvr':
predictors(x,  ...)

## S3 method for class 'gbm':
predictors(x,  ...)

## S3 method for class 'Weka_classifier':
predictors(x,  ...)

## S3 method for class 'fda':
predictors(x,  ...)

## S3 method for class 'earth':
predictors(x,  ...)

## S3 method for class 'gausspr':
predictors(x,  ...)

## S3 method for class 'ksvm':
predictors(x,  ...)

## S3 method for class 'lssvm':
predictors(x,  ...)

## S3 method for class 'rvm':
predictors(x,  ...)

## S3 method for class 'train':
predictors(x,  ...)

## S3 method for class 'gpls':
predictors(x,  ...)

## S3 method for class 'knn3':
predictors(x,  ...)

## S3 method for class 'LogitBoost':
predictors(x,  ...)

## S3 method for class 'lda':
predictors(x,  ...)

## S3 method for class 'rda':
predictors(x,  ...)

## S3 method for class 'multinom':
predictors(x,  ...)

## S3 method for class 'nnet':
predictors(x,  ...)

## S3 method for class 'pcaNNet':
predictors(x,  ...)

## S3 method for class 'NaiveBayes':
predictors(x,  ...)

## S3 method for class 'randomForest':
predictors(x,  ...)

## S3 method for class 'pamrtrained':
predictors(x, newdata = NULL, threshold = NULL, ...)

## S3 method for class 'superpc':
predictors(x, newdata = NULL, threshold = NULL, n.components = NULL, ...)

## S3 method for class 'slda':
predictors(x,  ...)

## S3 method for class 'rpart':
predictors(x, surrogate = TRUE,  ...)

## S3 method for class 'regbagg':
predictors(x, surrogate = TRUE,  ...)

## S3 method for class 'classbagg':
predictors(x, surrogate = TRUE,  ...)

## S3 method for class 'glmboost':
predictors(x,  ...)

## S3 method for class 'gamboost':
predictors(x,  ...)

## S3 method for class 'blackboost':
predictors(x,  ...)

## S3 method for class 'BinaryTree':
predictors(x, surrogate = TRUE,  ...)

## S3 method for class 'RandomForest':
predictors(x, surrogate = TRUE,  ...)

## S3 method for class 'bagEarth':
predictors(x,  ...)

## S3 method for class 'bagFDA':
predictors(x,  ...)

## S3 method for class 'ppr':
predictors(x,  ...)

Arguments

x a model object, list or terms
newdata for pamrtrained and superpc: the training data
threshold for pamrtrained and superpc: the feature selection threshold
n.components for superpc: the number of PCA components used
surrogate a logical for rpart, ipredbagg, bagging, BinaryTree and RandomForest: should variables used as surrogate splits also be returned?
... not currently used

Details

For randomForest, RandomForest, BinaryTree, rpart, ipredbagg, bagging, earth, fda, pamrtrained, superpc, bagEarth and bagFDA, an attempt was made to report the predictors that were actually used in the final model.

In cases where the predictors cannot be determined, NA is returned. For example, nnet.default may retrun missing values form predictors.

Value

a character string of predictors or NA.


[Package caret version 4.10 Index]