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caret (version 4.67)
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
4.67
License
GPL-2
Maintainer
Max Kuhn
Last Published
October 14th, 2010
Functions in caret (4.67)
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panel.needle
Needle Plot Lattice Panel
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
pcaNNet.default
Neural Networks with a Principal Component Step
sbfControl
Control Object for Selection By Filtering (SBF)
prcomp.resamples
Principal Components Analysis of Resampling Results
caretFuncs
Backwards Feature Selection Helper Functions
oneSE
Selecting tuning Parameters
predict.train
Extract predictions and class probabilities from train objects
classDist
Compute and predict the distances to class centroids
findCorrelation
Determine highly correlated variables
predict.knn3
Predictions from k-Nearest Neighbors
nullModel
Fit a simple, non-informative model
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
predict.bagEarth
Predicted values based on bagged Earth and FDA models
postResample
Calculates performance across resamples
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
tecator
Fat, Water and Protein Content of Meat Samples
cox2
COX-2 Activity Data
bagFDA
Bagged FDA
findLinearCombos
Determine linear combinations in a matrix
filterVarImp
Calculation of filter-based variable importance
knn3
k-Nearest Neighbour Classification
format.bagEarth
Format 'bagEarth' objects
varImp
Calculation of variable importance for regression and classification models
resamples
Collation and Visualization of Resampling Results
summary.bagEarth
Summarize a bagged earth or FDA fit
rfeControl
Controlling the Feature Selection Algorithms
roc
Compute the points for an ROC curve
applyProcessing
Data Processing on Predictor Variables (Deprecated)
as.table.confusionMatrix
Save Confusion Table Results
aucRoc
Compute the area under an ROC curve
cars
Kelly Blue Book resale data for 2005 model year GM cars
diff.resamples
Inferential Assessments About Model Performance
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
dotPlot
Create a dotplot of variable importance values
rfe
Backwards Feature Selection
print.train
Print Method for the train Class
sensitivity
Calculate sensitivity, specificity and predictive values
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
trainControl
Control parameters for train
bag.default
A General Framework For Bagging
plot.train
Plot Method for the train Class
oil
Fatty acid composition of commercial oils
preProcess
Pre-Processing of Predictors
resampleSummary
Summary of resampled performance estimates
predictors
List predictors used in the model
plot.varImp.train
Plotting variable importance measures
resampleHist
Plot the resampling distribution of the model statistics
train
Fit Predictive Models over Different Tuning Parameters
bagEarth
Bagged Earth
modelLookup
Descriptions Of Models Available in train()
dhfr
Dihydrofolate Reductase Inhibitors Data
histogram.train
Lattice functions for plotting resampling results
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
plotClassProbs
Plot Predicted Probabilities in Classification Models
print.confusionMatrix
Print method for confusionMatrix
createDataPartition
Data Splitting functions
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
knnreg
k-Nearest Neighbour Regression
nearZeroVar
Identification of near zero variance predictors
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
pottery
Pottery from Pre-Classical Sites in Italy
spatialSign
Compute the multivariate spatial sign
BloodBrain
Blood Brain Barrier Data
confusionMatrix
Create a confusion matrix
caret-internal
Internal Functions
GermanCredit
German Credit Data
createGrid
Tuning Parameter Grid
icr.formula
Independent Component Regression
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
sbf
Selection By Filtering (SBF)
maxDissim
Maximum Dissimilarity Sampling
caretSBF
Selection By Filtering (SBF) Helper Functions