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caret (version 6.0-21)
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
6.0-21
License
GPL-2
Maintainer
Max Kuhn
Last Published
January 4th, 2014
Functions in caret (6.0-21)
Search all functions
dummyVars
Create A Full Set of Dummy Variables
as.table.confusionMatrix
Save Confusion Table Results
lift
Lift Plot
knn3
k-Nearest Neighbour Classification
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
cars
Kelly Blue Book resale data for 2005 model year GM cars
predict.bagEarth
Predicted values based on bagged Earth and FDA models
bagEarth
Bagged Earth
diff.resamples
Inferential Assessments About Model Performance
panel.lift2
Lattice Panel Functions for Lift Plots
pottery
Pottery from Pre-Classical Sites in Italy
modelLookup
Tools for Models Available in
train
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
bag.default
A General Framework For Bagging
filterVarImp
Calculation of filter-based variable importance
GermanCredit
German Credit Data
BoxCoxTrans.default
Box-Cox and Exponential Transformations
avNNet.default
Neural Networks Using Model Averaging
cox2
COX-2 Activity Data
plotClassProbs
Plot Predicted Probabilities in Classification Models
prcomp.resamples
Principal Components Analysis of Resampling Results
oil
Fatty acid composition of commercial oils
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
dotPlot
Create a dotplot of variable importance values
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
classDist
Compute and predict the distances to class centroids
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
pcaNNet.default
Neural Networks with a Principal Component Step
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
nullModel
Fit a simple, non-informative model
format.bagEarth
Format 'bagEarth' objects
icr.formula
Independent Component Regression
findCorrelation
Determine highly correlated variables
plot.varImp.train
Plotting variable importance measures
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
confusionMatrix.train
Estimate a Resampled Confusion Matrix
caret-internal
Internal Functions
panel.needle
Needle Plot Lattice Panel
postResample
Calculates performance across resamples
print.train
Print Method for the train Class
resampleSummary
Summary of resampled performance estimates
preProcess
Pre-Processing of Predictors
predict.knn3
Predictions from k-Nearest Neighbors
maxDissim
Maximum Dissimilarity Sampling
rfe
Backwards Feature Selection
plot.train
Plot Method for the train Class
createDataPartition
Data Splitting functions
calibration
Probability Calibration Plot
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
rfeControl
Controlling the Feature Selection Algorithms
confusionMatrix
Create a confusion matrix
downSample
Down- and Up-Sampling Imbalanced Data
knnreg
k-Nearest Neighbour Regression
spatialSign
Compute the multivariate spatial sign
sensitivity
Calculate sensitivity, specificity and predictive values
update.train
Update or Re-fit a Model
resampleHist
Plot the resampling distribution of the model statistics
print.confusionMatrix
Print method for confusionMatrix
caretSBF
Selection By Filtering (SBF) Helper Functions
caretFuncs
Backwards Feature Selection Helper Functions
resamples
Collation and Visualization of Resampling Results
predictors
List predictors used in the model
sbf
Selection By Filtering (SBF)
trainControl
Control parameters for train
sbfControl
Control Object for Selection By Filtering (SBF)
tecator
Fat, Water and Protein Content of Meat Samples
oneSE
Selecting tuning Parameters
findLinearCombos
Determine linear combinations in a matrix
twoClassSim
Two-Class Simulations
histogram.train
Lattice functions for plotting resampling results
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
varImp
Calculation of variable importance for regression and classification models
plot.rfe
Plot RFE Performance Profiles
segmentationData
Cell Body Segmentation
BloodBrain
Blood Brain Barrier Data
bagFDA
Bagged FDA
nearZeroVar
Identification of near zero variance predictors
summary.bagEarth
Summarize a bagged earth or FDA fit
dhfr
Dihydrofolate Reductase Inhibitors Data
predict.train
Extract predictions and class probabilities from train objects
train
Fit Predictive Models over Different Tuning Parameters