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caret (version 4.51)
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
158,845
Version
4.51
License
GPL-2
Maintainer
Max Kuhn
Last Published
August 11th, 2010
Functions in caret (4.51)
Search all functions
predict.train
Extract predictions and class probabilities from train objects
dhfr
Dihydrofolate Reductase Inhibitors Data
rfe
Backwards Feature Selection
resampleSummary
Summary of resampled performance estimates
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
bag.default
A General Framework For Bagging
createGrid
Tuning Parameter Grid
nullModel
Fit a simple, non-informative model
knnreg
k-Nearest Neighbour Regression
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
pcaNNet.default
Neural Networks with a Principal Component Step
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
as.table.confusionMatrix
Save Confusion Table Results
bagEarth
Bagged Earth
aucRoc
Compute the area under an ROC curve
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
caret-internal
Internal Functions
cox2
COX-2 Activity Data
createDataPartition
Data Splitting functions
format.bagEarth
Format 'bagEarth' objects
resamples
Collation and Visualization of Resampling Results
nearZeroVar
Identification of near zero variance predictors
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
knn3
k-Nearest Neighbour Classification
applyProcessing
Data Processing on Predictor Variables (Deprecated)
findCorrelation
Determine highly correlated variables
plot.train
Plot Method for the train Class
confusionMatrix
Create a confusion matrix
spatialSign
Compute the multivariate spatial sign
diff.resamples
Inferential Assessments About Model Performance
oil
Fatty acid composition of commercial oils
print.train
Print Method for the train Class
print.confusionMatrix
Print method for confusionMatrix
maxDissim
Maximum Dissimilarity Sampling
plot.varImp.train
Plotting variable importance measures
predict.knn3
Predictions from k-Nearest Neighbors
roc
Compute the points for an ROC curve
predict.bagEarth
Predicted values based on bagged Earth and FDA models
rfeControl
Controlling the Feature Selection Algorithms
filterVarImp
Calculation of filter-based variable importance
panel.needle
Needle Plot Lattice Panel
train
Fit Predictive Models over Different Tuning Parameters
BloodBrain
Blood Brain Barrier Data
prcomp.resamples
Principal Components Analysis of Resampling Results
classDist
Compute and predict the distances to class centroids
varImp
Calculation of variable importance for regression and classification models
icr.formula
Independent Component Regression
sbf
Selection By Filtering (SBF)
tecator
Fat, Water and Protein Content of Meat Samples
pottery
Pottery from Pre-Classical Sites in Italy
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
trainControl
Control parameters for train
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
summary.bagEarth
Summarize a bagged earth or FDA fit
caretSBF
Selection By Filtering (SBF) Helper Functions
cars
Kelly Blue Book resale data for 2005 model year GM cars
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
dotPlot
Create a dotplot of variable importance values
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
postResample
Calculates performance across resamples
bagFDA
Bagged FDA
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
oneSE
Selecting tuning Parameters
GermanCredit
German Credit Data
plotClassProbs
Plot Predicted Probabilities in Classification Models
resampleHist
Plot the resampling distribution of the model statistics
predictors
List predictors used in the model
caretFuncs
Backwards Feature Selection Helper Functions
sensitivity
Calculate sensitivity, specificity and predictive values
findLinearCombos
Determine linear combinations in a matrix
histogram.train
Lattice functions for plotting resampling results
preProcess
Pre-Processing of Predictors
sbfControl
Control Object for Selection By Filtering (SBF)