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caret (version 5.01-001)
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
5.01-001
License
GPL-2
Maintainer
Max Kuhn
Last Published
September 2nd, 2011
Functions in caret (5.01-001)
Search all functions
cars
Kelly Blue Book resale data for 2005 model year GM cars
aucRoc
Compute the area under an ROC curve
bagEarth
Bagged Earth
nearZeroVar
Identification of near zero variance predictors
cox2
COX-2 Activity Data
print.train
Print Method for the train Class
resampleSummary
Summary of resampled performance estimates
bag.default
A General Framework For Bagging
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
BloodBrain
Blood Brain Barrier Data
predict.bagEarth
Predicted values based on bagged Earth and FDA models
filterVarImp
Calculation of filter-based variable importance
spatialSign
Compute the multivariate spatial sign
as.table.confusionMatrix
Save Confusion Table Results
findCorrelation
Determine highly correlated variables
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
createGrid
Tuning Parameter Grid
format.bagEarth
Format 'bagEarth' objects
predict.train
Extract predictions and class probabilities from train objects
dummyVars
Create A Full Set of Dummy Variables
confusionMatrix
Create a confusion matrix
plot.train
Plot Method for the train Class
pcaNNet.default
Neural Networks with a Principal Component Step
modelLookup
Descriptions Of Models Available in train()
rfe
Backwards Feature Selection
avNNet.default
Neural Networks Using Model Averaging
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
classDist
Compute and predict the distances to class centroids
caret-internal
Internal Functions
bagFDA
Bagged FDA
plotClassProbs
Plot Predicted Probabilities in Classification Models
nullModel
Fit a simple, non-informative model
createDataPartition
Data Splitting functions
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
prcomp.resamples
Principal Components Analysis of Resampling Results
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
maxDissim
Maximum Dissimilarity Sampling
oil
Fatty acid composition of commercial oils
sbfControl
Control Object for Selection By Filtering (SBF)
predict.knn3
Predictions from k-Nearest Neighbors
print.confusionMatrix
Print method for confusionMatrix
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
findLinearCombos
Determine linear combinations in a matrix
sbf
Selection By Filtering (SBF)
oneSE
Selecting tuning Parameters
preProcess
Pre-Processing of Predictors
knnreg
k-Nearest Neighbour Regression
icr.formula
Independent Component Regression
resampleHist
Plot the resampling distribution of the model statistics
predictors
List predictors used in the model
caretSBF
Selection By Filtering (SBF) Helper Functions
summary.bagEarth
Summarize a bagged earth or FDA fit
varImp
Calculation of variable importance for regression and classification models
GermanCredit
German Credit Data
trainControl
Control parameters for train
tecator
Fat, Water and Protein Content of Meat Samples
sensitivity
Calculate sensitivity, specificity and predictive values
knn3
k-Nearest Neighbour Classification
resamples
Collation and Visualization of Resampling Results
dhfr
Dihydrofolate Reductase Inhibitors Data
diff.resamples
Inferential Assessments About Model Performance
panel.needle
Needle Plot Lattice Panel
dotPlot
Create a dotplot of variable importance values
pottery
Pottery from Pre-Classical Sites in Italy
roc
Compute the points for an ROC curve
postResample
Calculates performance across resamples
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
caretFuncs
Backwards Feature Selection Helper Functions
segmentationData
Cell Body Segmentation
plot.varImp.train
Plotting variable importance measures
BoxCoxTrans.default
Box-Cox Transformations
confusionMatrix.train
Estimate a Resampled Confusion Matrix
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
histogram.train
Lattice functions for plotting resampling results
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
rfeControl
Controlling the Feature Selection Algorithms
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
train
Fit Predictive Models over Different Tuning Parameters