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caretEnsemble (version 1.0.0)

Ensembles of Caret Models

Description

Functions for creating ensembles of caret models: caretList, caretEnsemble, and caretStack. caretList is a convenience function for fitting multiple caret::train models to the same dataset. caretEnsemble will make a linear combination of these models using greedy forward selection, and caretStack will make linear or non-linear combinations of these models, using a caret::train model as a meta-model.

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Install

install.packages('caretEnsemble')

Monthly Downloads

2,144

Version

1.0.0

License

MIT + file LICENSE

Issues

6

Pull Requests

1

Stars

226

Forks

74

Maintainer

Zachary A Mayer

Last Published

January 16th, 2015

Functions in caretEnsemble (1.0.0)

extractCaretTarget.formula

Extracts the target variable from a set of arguments headed to the caret::train.formula function.
check_caretList_model_types

Checks that caretList models are all of the same type.
extractCaretTarget

Extracts the target variable from a set of arguments headed to the caret::train function.
extractBestPreds

Extract the best predictions from a list of train objects
residuals.caretEnsemble

Calculate the residuals from a caretEnsemble.
extractModelTypes

Extracts the model types from a list of train model
getMetric

Extract a model accuracy metric from an S3 object.
predict.caretEnsemble

Make predictions from a caretEnsemble. This function passes the data to each function in turn to make a matrix of predictions, and then multiplies that matrix by the vector of weights to get a single, combined vector of predictions.
multiResiduals

Calculate the residuals from all component models of a caretEnsemble.
caretEnsemble

Combine several predictive models via weights
dotplot.caretStack

Comparison dotplot for a caretStack object
wtd.sd

Calculate a weighted standard deviation
plot.caretStack

Plot a caretStack object
greedOptAUC

Greedy optimization of the area under the curve
makePredObsMatrix

Make a prediction matrix from a list of models
extractModRes

Extract the model accuracy metrics of the individual models in an ensemble object.
predict.caretStack

Make predictions from a caretStack
summary.caretStack

Summarize a caretStack object
tuneCheck

Check that the tuning parameters list supplied by the user is valid
trControlCheck

Check that the trainControl object supplied by the user is valid and has defined re-sampling indexes.
check_caretList_classes

Checks caretList model classes
check_bestpreds_obs

Check observeds
extractModFrame

Extract a dataframe of all predictors used in a caretEnsemble object.
plot.caretEnsemble

Plot Diagnostics for an caretEnsemble Object
check_bestpreds_indexes

Check row indexes
predict.caretList

Create a matrix of predictions for each of the models in a caretList
autoplot.caretEnsemble

Convenience function for more in-depth diagnostic plots of caretEnsemble objects
caretModelSpec

Generate a specification for fitting a caret model
caretList

Create a list of several train models from the caret package
varImp.caretEnsemble

Calculate the variable importance of variables in a caretEnsemble.
methodCheck

Check that the methods supplied by the user are valid caret methods
getMetricSD

Extract the standard deviation from resamples for an accuracy metric from a model object.
check_bestpreds_preds

Check predictions
extractCaretTarget.default

Extracts the target variable from a set of arguments headed to the caret::train.default function.
caretStack

Combine several predictive models via stacking
greedOptRMSE

Greedy optimization of the reduced mean square error
safeOptAUC

Safe optimization of the AUC
print.caretStack

Print a caretStack object
summary.caretEnsemble

Summarize the results of caretEnsemble for the user.
check_bestpreds_resamples

Check resamples
fortify.caretEnsemble

Supplement the data fitted to a caret ensemble model with model fit statistics