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caret (version 4.98)
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
4.98
License
GPL-2
Maintainer
Max Kuhn
Last Published
July 26th, 2011
Functions in caret (4.98)
Search all functions
confusionMatrix.train
Estimate a Resampled Confusion Matrix Using train
icr.formula
Independent Component Regression
bag.default
A General Framework For Bagging
print.train
Print Method for the train Class
maxDissim
Maximum Dissimilarity Sampling
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
pcaNNet.default
Neural Networks with a Principal Component Step
oneSE
Selecting tuning Parameters
confusionMatrix
Create a confusion matrix
summary.bagEarth
Summarize a bagged earth or FDA fit
classDist
Compute and predict the distances to class centroids
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
knnreg
k-Nearest Neighbour Regression
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
plot.varImp.train
Plotting variable importance measures
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
nearZeroVar
Identification of near zero variance predictors
caret-internal
Internal Functions
oil
Fatty acid composition of commercial oils
predictors
List predictors used in the model
nullModel
Fit a simple, non-informative model
as.table.confusionMatrix
Save Confusion Table Results
pottery
Pottery from Pre-Classical Sites in Italy
caretFuncs
Backwards Feature Selection Helper Functions
bagFDA
Bagged FDA
createGrid
Tuning Parameter Grid
dummyVars
Create A Full Set of Dummy Variables
cars
Kelly Blue Book resale data for 2005 model year GM cars
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
createDataPartition
Data Splitting functions
diff.resamples
Inferential Assessments About Model Performance
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
findLinearCombos
Determine linear combinations in a matrix
panel.needle
Needle Plot Lattice Panel
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
predict.bagEarth
Predicted values based on bagged Earth and FDA models
modelLookup
Descriptions Of Models Available in train()
bagEarth
Bagged Earth
resampleHist
Plot the resampling distribution of the model statistics
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
filterVarImp
Calculation of filter-based variable importance
knn3
k-Nearest Neighbour Classification
plotClassProbs
Plot Predicted Probabilities in Classification Models
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
postResample
Calculates performance across resamples
caretSBF
Selection By Filtering (SBF) Helper Functions
tecator
Fat, Water and Protein Content of Meat Samples
print.confusionMatrix
Print method for confusionMatrix
varImp
Calculation of variable importance for regression and classification models
GermanCredit
German Credit Data
spatialSign
Compute the multivariate spatial sign
avNNet.default
Neural Networks Using Model Averaging
dotPlot
Create a dotplot of variable importance values
sensitivity
Calculate sensitivity, specificity and predictive values
predict.knn3
Predictions from k-Nearest Neighbors
findCorrelation
Determine highly correlated variables
prcomp.resamples
Principal Components Analysis of Resampling Results
trainControl
Control parameters for train
train
Fit Predictive Models over Different Tuning Parameters
plot.train
Plot Method for the train Class
rfe
Backwards Feature Selection
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
segmentationData
Cell Body Segmentation
predict.train
Extract predictions and class probabilities from train objects
resampleSummary
Summary of resampled performance estimates
resamples
Collation and Visualization of Resampling Results
histogram.train
Lattice functions for plotting resampling results
sbf
Selection By Filtering (SBF)
aucRoc
Compute the area under an ROC curve
BloodBrain
Blood Brain Barrier Data
sbfControl
Control Object for Selection By Filtering (SBF)
dhfr
Dihydrofolate Reductase Inhibitors Data
BoxCoxTrans.default
Box-Cox Transformations
cox2
COX-2 Activity Data
format.bagEarth
Format 'bagEarth' objects
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
preProcess
Pre-Processing of Predictors
rfeControl
Controlling the Feature Selection Algorithms
roc
Compute the points for an ROC curve