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caret (version 4.90)
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
160,352
Version
4.90
License
GPL-2
Maintainer
Max Kuhn
Last Published
June 2nd, 2011
Functions in caret (4.90)
Search functions
nearZeroVar
Identification of near zero variance predictors
as.table.confusionMatrix
Save Confusion Table Results
BoxCoxTrans.default
Box-Cox Transformations
applyProcessing
Data Processing on Predictor Variables (Deprecated)
cox2
COX-2 Activity Data
cars
Kelly Blue Book resale data for 2005 model year GM cars
panel.needle
Needle Plot Lattice Panel
caretFuncs
Backwards Feature Selection Helper Functions
diff.resamples
Inferential Assessments About Model Performance
predict.knn3
Predictions from k-Nearest Neighbors
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
modelLookup
Descriptions Of Models Available in train()
format.bagEarth
Format 'bagEarth' objects
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
tecator
Fat, Water and Protein Content of Meat Samples
bag.default
A General Framework For Bagging
spatialSign
Compute the multivariate spatial sign
findLinearCombos
Determine linear combinations in a matrix
sbf
Selection By Filtering (SBF)
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
aucRoc
Compute the area under an ROC curve
icr.formula
Independent Component Regression
plotClassProbs
Plot Predicted Probabilities in Classification Models
createDataPartition
Data Splitting functions
histogram.train
Lattice functions for plotting resampling results
postResample
Calculates performance across resamples
createGrid
Tuning Parameter Grid
pcaNNet.default
Neural Networks with a Principal Component Step
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
caret-internal
Internal Functions
bagFDA
Bagged FDA
findCorrelation
Determine highly correlated variables
dhfr
Dihydrofolate Reductase Inhibitors Data
dummyVars
Create A Full Set of Dummy Variables
roc
Compute the points for an ROC curve
predict.train
Extract predictions and class probabilities from train objects
knnreg
k-Nearest Neighbour Regression
confusionMatrix
Create a confusion matrix
trainControl
Control parameters for train
BloodBrain
Blood Brain Barrier Data
prcomp.resamples
Principal Components Analysis of Resampling Results
plot.train
Plot Method for the train Class
maxDissim
Maximum Dissimilarity Sampling
knn3
k-Nearest Neighbour Classification
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
print.train
Print Method for the train Class
dotPlot
Create a dotplot of variable importance values
nullModel
Fit a simple, non-informative model
filterVarImp
Calculation of filter-based variable importance
resampleHist
Plot the resampling distribution of the model statistics
sensitivity
Calculate sensitivity, specificity and predictive values
train
Fit Predictive Models over Different Tuning Parameters
rfeControl
Controlling the Feature Selection Algorithms
segmentationData
Cell Body Segmentation
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
sbfControl
Control Object for Selection By Filtering (SBF)
rfe
Backwards Feature Selection
resampleSummary
Summary of resampled performance estimates
plot.varImp.train
Plotting variable importance measures
print.confusionMatrix
Print method for confusionMatrix
resamples
Collation and Visualization of Resampling Results
varImp
Calculation of variable importance for regression and classification models
summary.bagEarth
Summarize a bagged earth or FDA fit
GermanCredit
German Credit Data
bagEarth
Bagged Earth
predict.bagEarth
Predicted values based on bagged Earth and FDA models
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
classDist
Compute and predict the distances to class centroids
oneSE
Selecting tuning Parameters
predictors
List predictors used in the model
oil
Fatty acid composition of commercial oils
caretSBF
Selection By Filtering (SBF) Helper Functions
preProcess
Pre-Processing of Predictors
pottery
Pottery from Pre-Classical Sites in Italy
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution