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caret (version 5.15-023)
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
5.15-023
License
GPL-2
Maintainer
Max Kuhn
Last Published
March 20th, 2012
Functions in caret (5.15-023)
Search all functions
BoxCoxTrans.default
Box-Cox Transformations
bag.default
A General Framework For Bagging
findLinearCombos
Determine linear combinations in a matrix
plot.train
Plot Method for the train Class
oneSE
Selecting tuning Parameters
BloodBrain
Blood Brain Barrier Data
knnreg
k-Nearest Neighbour Regression
icr.formula
Independent Component Regression
maxDissim
Maximum Dissimilarity Sampling
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
knn3
k-Nearest Neighbour Classification
sbf
Selection By Filtering (SBF)
rfeControl
Controlling the Feature Selection Algorithms
pcaNNet.default
Neural Networks with a Principal Component Step
as.table.confusionMatrix
Save Confusion Table Results
avNNet.default
Neural Networks Using Model Averaging
filterVarImp
Calculation of filter-based variable importance
confusionMatrix
Create a confusion matrix
cars
Kelly Blue Book resale data for 2005 model year GM cars
dotPlot
Create a dotplot of variable importance values
caret-internal
Internal Functions
predict.train
Extract predictions and class probabilities from train objects
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
bagEarth
Bagged Earth
calibration
Probability Calibration Plot
panel.needle
Needle Plot Lattice Panel
diff.resamples
Inferential Assessments About Model Performance
resampleSummary
Summary of resampled performance estimates
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
postResample
Calculates performance across resamples
bagFDA
Bagged FDA
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
segmentationData
Cell Body Segmentation
GermanCredit
German Credit Data
format.bagEarth
Format 'bagEarth' objects
nearZeroVar
Identification of near zero variance predictors
spatialSign
Compute the multivariate spatial sign
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
classDist
Compute and predict the distances to class centroids
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
plotClassProbs
Plot Predicted Probabilities in Classification Models
oil
Fatty acid composition of commercial oils
print.confusionMatrix
Print method for confusionMatrix
sensitivity
Calculate sensitivity, specificity and predictive values
update.train
Update and Re-fit a Model
varImp
Calculation of variable importance for regression and classification models
dummyVars
Create A Full Set of Dummy Variables
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
predict.knn3
Predictions from k-Nearest Neighbors
caretSBF
Selection By Filtering (SBF) Helper Functions
modelLookup
Descriptions Of Models Available in train()
tecator
Fat, Water and Protein Content of Meat Samples
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
prcomp.resamples
Principal Components Analysis of Resampling Results
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
sbfControl
Control Object for Selection By Filtering (SBF)
histogram.train
Lattice functions for plotting resampling results
lift
Lift Plot
print.train
Print Method for the train Class
plot.varImp.train
Plotting variable importance measures
resamples
Collation and Visualization of Resampling Results
pottery
Pottery from Pre-Classical Sites in Italy
confusionMatrix.train
Estimate a Resampled Confusion Matrix
createDataPartition
Data Splitting functions
nullModel
Fit a simple, non-informative model
caretFuncs
Backwards Feature Selection Helper Functions
resampleHist
Plot the resampling distribution of the model statistics
dhfr
Dihydrofolate Reductase Inhibitors Data
panel.lift2
Lattice Panel Functions for Lift Plots
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
predict.bagEarth
Predicted values based on bagged Earth and FDA models
rfe
Backwards Feature Selection
cox2
COX-2 Activity Data
createGrid
Tuning Parameter Grid
findCorrelation
Determine highly correlated variables
summary.bagEarth
Summarize a bagged earth or FDA fit
trainControl
Control parameters for train
preProcess
Pre-Processing of Predictors
predictors
List predictors used in the model