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caret (version 4.48)
Classification and Regression Training
Description
Misc functions for training and plotting classification and regression models
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Install
install.packages('caret')
Monthly Downloads
231,168
Version
4.48
License
GPL-2
Maintainer
Max Kuhn
Last Published
August 8th, 2010
Functions in caret (4.48)
Search all functions
applyProcessing
Data Processing on Predictor Variables (Deprecated)
cox2
COX-2 Activity Data
preProcess
Pre-Processing of Predictors
rfe
Backwards Feature Selection
bag.default
A General Framework For Bagging
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
histogram.train
Lattice functions for plotting resampling results
postResample
Calculates performance across resamples
sbfControl
Control Object for Selection By Filtering (SBF)
print.train
Print Method for the train Class
findCorrelation
Determine highly correlated variables
icr.formula
Independent Component Regression
predict.bagEarth
Predicted values based on bagged Earth and FDA models
nearZeroVar
Identification of near zero variance predictors
roc
Compute the points for an ROC curve
sensitivity
Calculate sensitivity, specificity and predictive values
resamples
Collation and Visualization of Resampling Results
trainControl
Control parameters for train
caretSBF
Selection By Filtering (SBF) Helper Functions
caret-internal
Internal Functions
BloodBrain
Blood Brain Barrier Data
createDataPartition
Data Splitting functions
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
knn3
k-Nearest Neighbour Classification
predict.knn3
Predictions from k-Nearest Neighbors
bagEarth
Bagged Earth
as.table.confusionMatrix
Save Confusion Table Results
dotPlot
Create a dotplot of variable importance values
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
plot.varImp.train
Plotting variable importance measures
varImp
Calculation of variable importance for regression and classification models
print.confusionMatrix
Print method for confusionMatrix
train
Fit Predictive Models over Different Tuning Parameters
GermanCredit
German Credit Data
confusionMatrix
Create a confusion matrix
dhfr
Dihydrofolate Reductase Inhibitors Data
cars
Kelly Blue Book resale data for 2005 model year GM cars
oil
Fatty acid composition of commercial oils
panel.needle
Needle Plot Lattice Panel
summary.bagEarth
Summarize a bagged earth or FDA fit
classDist
Compute and predict the distances to class centroids
predict.train
Extract predictions and class probabilities from train objects
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
nullModel
Fit a simple, non-informative model
predictors
List predictors used in the model
sbf
Selection By Filtering (SBF)
filterVarImp
Calculation of filter-based variable importance
format.bagEarth
Format 'bagEarth' objects
plotClassProbs
Plot Predicted Probabilities in Classification Models
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
knnreg
k-Nearest Neighbour Regression
resampleHist
Plot the resampling distribution of the model statistics
pcaNNet.default
Neural Networks with a Principal Component Step
createGrid
Tuning Parameter Grid
maxDissim
Maximum Dissimilarity Sampling
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
resampleSummary
Summary of resampled performance estimates
tecator
Fat, Water and Protein Content of Meat Samples
caretFuncs
Backwards Feature Selection Helper Functions
spatialSign
Compute the multivariate spatial sign
plot.train
Plot Method for the train Class
oneSE
Selecting tuning Parameters
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
diff.resamples
Inferential Assessments About Model Performance
aucRoc
Compute the area under an ROC curve
bagFDA
Bagged FDA
findLinearCombos
Determine linear combinations in a matrix
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
prcomp.resamples
Principal Components Analysis of Resampling Results
pottery
Pottery from Pre-Classical Sites in Italy
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
rfeControl
Controlling the Feature Selection Algorithms