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caret (version 4.70)
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
4.70
License
GPL-2
Maintainer
Max Kuhn
Last Published
November 10th, 2010
Functions in caret (4.70)
Search all functions
caret-internal
Internal Functions
bagFDA
Bagged FDA
cars
Kelly Blue Book resale data for 2005 model year GM cars
filterVarImp
Calculation of filter-based variable importance
cox2
COX-2 Activity Data
findLinearCombos
Determine linear combinations in a matrix
icr.formula
Independent Component Regression
knnreg
k-Nearest Neighbour Regression
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
nullModel
Fit a simple, non-informative model
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
plot.varImp.train
Plotting variable importance measures
bagEarth
Bagged Earth
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
classDist
Compute and predict the distances to class centroids
resamples
Collation and Visualization of Resampling Results
rfe
Backwards Feature Selection
caretSBF
Selection By Filtering (SBF) Helper Functions
spatialSign
Compute the multivariate spatial sign
predict.train
Extract predictions and class probabilities from train objects
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
knn3
k-Nearest Neighbour Classification
panel.needle
Needle Plot Lattice Panel
plotClassProbs
Plot Predicted Probabilities in Classification Models
trainControl
Control parameters for train
as.table.confusionMatrix
Save Confusion Table Results
createDataPartition
Data Splitting functions
dotPlot
Create a dotplot of variable importance values
dhfr
Dihydrofolate Reductase Inhibitors Data
modelLookup
Descriptions Of Models Available in train()
maxDissim
Maximum Dissimilarity Sampling
histogram.train
Lattice functions for plotting resampling results
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
predict.knn3
Predictions from k-Nearest Neighbors
applyProcessing
Data Processing on Predictor Variables (Deprecated)
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
nearZeroVar
Identification of near zero variance predictors
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
createGrid
Tuning Parameter Grid
diff.resamples
Inferential Assessments About Model Performance
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
print.confusionMatrix
Print method for confusionMatrix
bag.default
A General Framework For Bagging
GermanCredit
German Credit Data
predict.bagEarth
Predicted values based on bagged Earth and FDA models
pottery
Pottery from Pre-Classical Sites in Italy
prcomp.resamples
Principal Components Analysis of Resampling Results
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
sensitivity
Calculate sensitivity, specificity and predictive values
postResample
Calculates performance across resamples
oil
Fatty acid composition of commercial oils
tecator
Fat, Water and Protein Content of Meat Samples
sbf
Selection By Filtering (SBF)
preProcess
Pre-Processing of Predictors
oneSE
Selecting tuning Parameters
confusionMatrix
Create a confusion matrix
summary.bagEarth
Summarize a bagged earth or FDA fit
findCorrelation
Determine highly correlated variables
roc
Compute the points for an ROC curve
resampleHist
Plot the resampling distribution of the model statistics
BloodBrain
Blood Brain Barrier Data
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
resampleSummary
Summary of resampled performance estimates
segmentationData
Cell Body Segmentation
rfeControl
Controlling the Feature Selection Algorithms
format.bagEarth
Format 'bagEarth' objects
aucRoc
Compute the area under an ROC curve
predictors
List predictors used in the model
pcaNNet.default
Neural Networks with a Principal Component Step
print.train
Print Method for the train Class
train
Fit Predictive Models over Different Tuning Parameters
sbfControl
Control Object for Selection By Filtering (SBF)
plot.train
Plot Method for the train Class
varImp
Calculation of variable importance for regression and classification models
caretFuncs
Backwards Feature Selection Helper Functions