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caret (version 5.04-007)
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
5.04-007
License
GPL-2
Maintainer
Max Kuhn
Last Published
September 27th, 2011
Functions in caret (5.04-007)
Search all functions
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
cox2
COX-2 Activity Data
postResample
Calculates performance across resamples
print.confusionMatrix
Print method for confusionMatrix
trainControl
Control parameters for train
aucRoc
Compute the area under an ROC curve
confusionMatrix.train
Estimate a Resampled Confusion Matrix
createGrid
Tuning Parameter Grid
diff.resamples
Inferential Assessments About Model Performance
filterVarImp
Calculation of filter-based variable importance
avNNet.default
Neural Networks Using Model Averaging
GermanCredit
German Credit Data
createDataPartition
Data Splitting functions
plot.varImp.train
Plotting variable importance measures
nearZeroVar
Identification of near zero variance predictors
prcomp.resamples
Principal Components Analysis of Resampling Results
findLinearCombos
Determine linear combinations in a matrix
resampleHist
Plot the resampling distribution of the model statistics
icr.formula
Independent Component Regression
bag.default
A General Framework For Bagging
histogram.train
Lattice functions for plotting resampling results
sensitivity
Calculate sensitivity, specificity and predictive values
predict.train
Extract predictions and class probabilities from train objects
knn3
k-Nearest Neighbour Classification
knnreg
k-Nearest Neighbour Regression
caret-internal
Internal Functions
oil
Fatty acid composition of commercial oils
oneSE
Selecting tuning Parameters
cars
Kelly Blue Book resale data for 2005 model year GM cars
bagFDA
Bagged FDA
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
preProcess
Pre-Processing of Predictors
segmentationData
Cell Body Segmentation
confusionMatrix
Create a confusion matrix
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
BoxCoxTrans.default
Box-Cox Transformations
classDist
Compute and predict the distances to class centroids
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
maxDissim
Maximum Dissimilarity Sampling
sbfControl
Control Object for Selection By Filtering (SBF)
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
sbf
Selection By Filtering (SBF)
print.train
Print Method for the train Class
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
modelLookup
Descriptions Of Models Available in train()
predict.knn3
Predictions from k-Nearest Neighbors
panel.lift2
Lattice Panel Functions for Lift Plots
summary.bagEarth
Summarize a bagged earth or FDA fit
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
panel.needle
Needle Plot Lattice Panel
rfe
Backwards Feature Selection
dummyVars
Create A Full Set of Dummy Variables
predictors
List predictors used in the model
pcaNNet.default
Neural Networks with a Principal Component Step
plot.train
Plot Method for the train Class
format.bagEarth
Format 'bagEarth' objects
spatialSign
Compute the multivariate spatial sign
varImp
Calculation of variable importance for regression and classification models
tecator
Fat, Water and Protein Content of Meat Samples
roc
Compute the points for an ROC curve
nullModel
Fit a simple, non-informative model
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
resamples
Collation and Visualization of Resampling Results
dhfr
Dihydrofolate Reductase Inhibitors Data
predict.bagEarth
Predicted values based on bagged Earth and FDA models
as.table.confusionMatrix
Save Confusion Table Results
rfeControl
Controlling the Feature Selection Algorithms
caretSBF
Selection By Filtering (SBF) Helper Functions
BloodBrain
Blood Brain Barrier Data
bagEarth
Bagged Earth
dotPlot
Create a dotplot of variable importance values
findCorrelation
Determine highly correlated variables
lift
Lift Plot
plotClassProbs
Plot Predicted Probabilities in Classification Models
pottery
Pottery from Pre-Classical Sites in Italy
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
resampleSummary
Summary of resampled performance estimates
caretFuncs
Backwards Feature Selection Helper Functions
train
Fit Predictive Models over Different Tuning Parameters