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caret (version 4.59)
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
163,965
Version
4.59
License
GPL-2
Maintainer
Max Kuhn
Last Published
September 1st, 2010
Functions in caret (4.59)
Search all functions
aucRoc
Compute the area under an ROC curve
as.table.confusionMatrix
Save Confusion Table Results
bag.default
A General Framework For Bagging
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
cox2
COX-2 Activity Data
knnreg
k-Nearest Neighbour Regression
spatialSign
Compute the multivariate spatial sign
confusionMatrix
Create a confusion matrix
predict.train
Extract predictions and class probabilities from train objects
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
BloodBrain
Blood Brain Barrier Data
predict.knn3
Predictions from k-Nearest Neighbors
trainControl
Control parameters for train
findLinearCombos
Determine linear combinations in a matrix
format.bagEarth
Format 'bagEarth' objects
resamples
Collation and Visualization of Resampling Results
resampleHist
Plot the resampling distribution of the model statistics
sbfControl
Control Object for Selection By Filtering (SBF)
tecator
Fat, Water and Protein Content of Meat Samples
caretSBF
Selection By Filtering (SBF) Helper Functions
bagEarth
Bagged Earth
knn3
k-Nearest Neighbour Classification
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
modelLookup
Descriptions Of Models Available in train()
predict.bagEarth
Predicted values based on bagged Earth and FDA models
preProcess
Pre-Processing of Predictors
oneSE
Selecting tuning Parameters
createGrid
Tuning Parameter Grid
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
rfe
Backwards Feature Selection
sbf
Selection By Filtering (SBF)
summary.bagEarth
Summarize a bagged earth or FDA fit
classDist
Compute and predict the distances to class centroids
nullModel
Fit a simple, non-informative model
roc
Compute the points for an ROC curve
pcaNNet.default
Neural Networks with a Principal Component Step
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
caret-internal
Internal Functions
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
maxDissim
Maximum Dissimilarity Sampling
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
filterVarImp
Calculation of filter-based variable importance
findCorrelation
Determine highly correlated variables
print.confusionMatrix
Print method for confusionMatrix
plot.train
Plot Method for the train Class
rfeControl
Controlling the Feature Selection Algorithms
sensitivity
Calculate sensitivity, specificity and predictive values
varImp
Calculation of variable importance for regression and classification models
train
Fit Predictive Models over Different Tuning Parameters
applyProcessing
Data Processing on Predictor Variables (Deprecated)
bagFDA
Bagged FDA
dhfr
Dihydrofolate Reductase Inhibitors Data
icr.formula
Independent Component Regression
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
plot.varImp.train
Plotting variable importance measures
prcomp.resamples
Principal Components Analysis of Resampling Results
oil
Fatty acid composition of commercial oils
postResample
Calculates performance across resamples
print.train
Print Method for the train Class
caretFuncs
Backwards Feature Selection Helper Functions
nearZeroVar
Identification of near zero variance predictors
diff.resamples
Inferential Assessments About Model Performance
panel.needle
Needle Plot Lattice Panel
pottery
Pottery from Pre-Classical Sites in Italy
resampleSummary
Summary of resampled performance estimates
GermanCredit
German Credit Data
cars
Kelly Blue Book resale data for 2005 model year GM cars
createDataPartition
Data Splitting functions
dotPlot
Create a dotplot of variable importance values
histogram.train
Lattice functions for plotting resampling results
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
plotClassProbs
Plot Predicted Probabilities in Classification Models
predictors
List predictors used in the model
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models