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caret (version 4.68)
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
4.68
License
GPL-2
Maintainer
Max Kuhn
Last Published
October 23rd, 2010
Functions in caret (4.68)
Search functions
cox2
COX-2 Activity Data
dotPlot
Create a dotplot of variable importance values
pottery
Pottery from Pre-Classical Sites in Italy
resampleHist
Plot the resampling distribution of the model statistics
summary.bagEarth
Summarize a bagged earth or FDA fit
sbfControl
Control Object for Selection By Filtering (SBF)
aucRoc
Compute the area under an ROC curve
applyProcessing
Data Processing on Predictor Variables (Deprecated)
histogram.train
Lattice functions for plotting resampling results
bagFDA
Bagged FDA
GermanCredit
German Credit Data
pcaNNet.default
Neural Networks with a Principal Component Step
print.confusionMatrix
Print method for confusionMatrix
nearZeroVar
Identification of near zero variance predictors
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
postResample
Calculates performance across resamples
findLinearCombos
Determine linear combinations in a matrix
format.bagEarth
Format 'bagEarth' objects
knnreg
k-Nearest Neighbour Regression
preProcess
Pre-Processing of Predictors
print.train
Print Method for the train Class
diff.resamples
Inferential Assessments About Model Performance
BloodBrain
Blood Brain Barrier Data
modelLookup
Descriptions Of Models Available in train()
caretFuncs
Backwards Feature Selection Helper Functions
knn3
k-Nearest Neighbour Classification
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
rfeControl
Controlling the Feature Selection Algorithms
segmentationData
Cell Body Segmentation
caret-internal
Internal Functions
sbf
Selection By Filtering (SBF)
oneSE
Selecting tuning Parameters
createGrid
Tuning Parameter Grid
findCorrelation
Determine highly correlated variables
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
predict.bagEarth
Predicted values based on bagged Earth and FDA models
sensitivity
Calculate sensitivity, specificity and predictive values
train
Fit Predictive Models over Different Tuning Parameters
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
icr.formula
Independent Component Regression
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
plot.train
Plot Method for the train Class
plot.varImp.train
Plotting variable importance measures
predict.knn3
Predictions from k-Nearest Neighbors
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
resamples
Collation and Visualization of Resampling Results
plotClassProbs
Plot Predicted Probabilities in Classification Models
bagEarth
Bagged Earth
classDist
Compute and predict the distances to class centroids
predict.train
Extract predictions and class probabilities from train objects
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
dhfr
Dihydrofolate Reductase Inhibitors Data
bag.default
A General Framework For Bagging
cars
Kelly Blue Book resale data for 2005 model year GM cars
prcomp.resamples
Principal Components Analysis of Resampling Results
rfe
Backwards Feature Selection
roc
Compute the points for an ROC curve
spatialSign
Compute the multivariate spatial sign
confusionMatrix
Create a confusion matrix
as.table.confusionMatrix
Save Confusion Table Results
filterVarImp
Calculation of filter-based variable importance
maxDissim
Maximum Dissimilarity Sampling
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
panel.needle
Needle Plot Lattice Panel
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
predictors
List predictors used in the model
tecator
Fat, Water and Protein Content of Meat Samples
createDataPartition
Data Splitting functions
nullModel
Fit a simple, non-informative model
caretSBF
Selection By Filtering (SBF) Helper Functions
resampleSummary
Summary of resampled performance estimates
oil
Fatty acid composition of commercial oils
varImp
Calculation of variable importance for regression and classification models
trainControl
Control parameters for train