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caret (version 4.23)
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
138,220
Version
4.23
License
GPL-2
Maintainer
Max Kuhn
Last Published
September 28th, 2009
Functions in caret (4.23)
Search all functions
knn3
k-Nearest Neighbour Classification
oil
Fatty acid composition of commercial oils
createDataPartition
Data Splitting functions
nearZeroVar
Identification of near zero variance predictors
cox2
COX-2 Activity Data
dotPlot
Create a dotplot of variable importance values
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
predictors
List predictors used in the model
createGrid
Tuning Parameter Grid
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
BloodBrain
Blood Brain Barrier Data
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
pottery
Pottery from Pre-Classical Sites in Italy
findLinearCombos
Determine linear combinations in a matrix
aucRoc
Compute the area under an ROC curve
findCorrelation
Determine highly correlated variables
filterVarImp
Calculation of filter-based variable importance
roc
Compute the points for an ROC curve
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
postResample
Calculates performance across resamples
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
confusionMatrix
Create a confusion matrix
knnreg
k-Nearest Neighbour Regression
applyProcessing
Data Processing on Predictor Variables (Deprecated)
caret-internal
Internal Functions
plotClassProbs
Plot Predicted Probabilities in Classification Models
rfeControl
Controlling the Feature Selection Algorithms
bagEarth
Bagged Earth
histogram.train
Lattice functions for plotting resampling results
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
sensitivity
Calculate sensitivity, specificity and predictive values
maxDissim
Maximum Dissimilarity Sampling
panel.needle
Needle Plot Lattice Panel
rfe
Backwards Feature Selection
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
as.table.confusionMatrix
Save Confusion Table Results
trainControl
Control parameters for train
caretFuncs
Backwards Feature Selection Helper Functions
resampleHist
Plot the resampling distribution of the model statistics
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
plot.varImp.train
Plotting variable importance measures
print.train
Print Method for the train Class
predict.train
Extract predictions and class probabilities from train objects
bagFDA
Bagged FDA
format.bagEarth
Format 'bagEarth' objects
preProcess
Pre-Processing of Predictors
predict.bagEarth
Predicted values based on bagged Earth and FDA models
varImp
Calculation of variable importance for regression and classification models
pcaNNet.default
Neural Networks with a Principal Component Step
train
Fit Predictive Models over Different Tuning Parameters
spatialSign
Compute the multivariate spatial sign
resampleSummary
Summary of resampled performance estimates
tecator
Fat, Water and Protein Content of Maat Samples
oneSE
Selecting tuning Parameters
summary.bagEarth
Summarize a bagged earth or FDA fit
print.confusionMatrix
Print method for confusionMatrix
classDist
Compute and predict the distances to class centroids
plot.train
Plot Method for the train Class
predict.knn3
Predictions from k-Nearest Neighbors