predictors {caret} | R Documentation |
This class uses a model fit to determine which predictors were used in the final model.
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, ...)
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 |
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
.
a character string of predictors or NA
.