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caret (version 4.54)
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
4.54
License
GPL-2
Maintainer
Max Kuhn
Last Published
August 18th, 2010
Functions in caret (4.54)
Search all functions
createGrid
Tuning Parameter Grid
panel.needle
Needle Plot Lattice Panel
classDist
Compute and predict the distances to class centroids
print.confusionMatrix
Print method for confusionMatrix
trainControl
Control parameters for train
oneSE
Selecting tuning Parameters
cars
Kelly Blue Book resale data for 2005 model year GM cars
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
findLinearCombos
Determine linear combinations in a matrix
GermanCredit
German Credit Data
dotPlot
Create a dotplot of variable importance values
findCorrelation
Determine highly correlated variables
knn3
k-Nearest Neighbour Classification
bag.default
A General Framework For Bagging
resamples
Collation and Visualization of Resampling Results
sbf
Selection By Filtering (SBF)
preProcess
Pre-Processing of Predictors
BloodBrain
Blood Brain Barrier Data
format.bagEarth
Format 'bagEarth' objects
diff.resamples
Inferential Assessments About Model Performance
knnreg
k-Nearest Neighbour Regression
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
prcomp.resamples
Principal Components Analysis of Resampling Results
tecator
Fat, Water and Protein Content of Meat Samples
train
Fit Predictive Models over Different Tuning Parameters
cox2
COX-2 Activity Data
applyProcessing
Data Processing on Predictor Variables (Deprecated)
icr.formula
Independent Component Regression
bagFDA
Bagged FDA
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
caret-internal
Internal Functions
nearZeroVar
Identification of near zero variance predictors
pcaNNet.default
Neural Networks with a Principal Component Step
dhfr
Dihydrofolate Reductase Inhibitors Data
caretFuncs
Backwards Feature Selection Helper Functions
plot.varImp.train
Plotting variable importance measures
sbfControl
Control Object for Selection By Filtering (SBF)
varImp
Calculation of variable importance for regression and classification models
summary.bagEarth
Summarize a bagged earth or FDA fit
rfeControl
Controlling the Feature Selection Algorithms
spatialSign
Compute the multivariate spatial sign
rfe
Backwards Feature Selection
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
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
postResample
Calculates performance across resamples
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
caretSBF
Selection By Filtering (SBF) Helper Functions
as.table.confusionMatrix
Save Confusion Table Results
createDataPartition
Data Splitting functions
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
filterVarImp
Calculation of filter-based variable importance
nullModel
Fit a simple, non-informative model
oil
Fatty acid composition of commercial oils
predict.knn3
Predictions from k-Nearest Neighbors
pottery
Pottery from Pre-Classical Sites in Italy
resampleHist
Plot the resampling distribution of the model statistics
print.train
Print Method for the train Class
predictors
List predictors used in the model
sensitivity
Calculate sensitivity, specificity and predictive values
aucRoc
Compute the area under an ROC curve
bagEarth
Bagged Earth
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
confusionMatrix
Create a confusion matrix
roc
Compute the points for an ROC curve
resampleSummary
Summary of resampled performance estimates
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
predict.train
Extract predictions and class probabilities from train objects
maxDissim
Maximum Dissimilarity Sampling
plot.train
Plot Method for the train Class
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
predict.bagEarth
Predicted values based on bagged Earth and FDA models