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caret (version 4.37)
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
4.37
License
GPL-2
Maintainer
Max Kuhn
Last Published
April 19th, 2010
Functions in caret (4.37)
Search all functions
createGrid
Tuning Parameter Grid
createDataPartition
Data Splitting functions
filterVarImp
Calculation of filter-based variable importance
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
pcaNNet.default
Neural Networks with a Principal Component Step
print.confusionMatrix
Print method for confusionMatrix
bagEarth
Bagged Earth
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
predict.bagEarth
Predicted values based on bagged Earth and FDA models
nullModel
Fit a simple, non-informative model
aucRoc
Compute the area under an ROC curve
findLinearCombos
Determine linear combinations in a matrix
confusionMatrix
Create a confusion matrix
findCorrelation
Determine highly correlated variables
panel.needle
Needle Plot Lattice Panel
oil
Fatty acid composition of commercial oils
maxDissim
Maximum Dissimilarity Sampling
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
resampleHist
Plot the resampling distribution of the model statistics
histogram.train
Lattice functions for plotting resampling results
postResample
Calculates performance across resamples
plot.varImp.train
Plotting variable importance measures
sensitivity
Calculate sensitivity, specificity and predictive values
tecator
Fat, Water and Protein Content of Meat Samples
caretSBF
Selection By Filtering (SBF) Helper Functions
predict.train
Extract predictions and class probabilities from train objects
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
cox2
COX-2 Activity Data
rfeControl
Controlling the Feature Selection Algorithms
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
roc
Compute the points for an ROC curve
oneSE
Selecting tuning Parameters
classDist
Compute and predict the distances to class centroids
caret-internal
Internal Functions
sbfControl
Control Object for Selection By Filtering (SBF)
dhfr
Dihydrofolate Reductase Inhibitors Data
knnreg
k-Nearest Neighbour Regression
preProcess
Pre-Processing of Predictors
rfe
Backwards Feature Selection
bagFDA
Bagged FDA
nearZeroVar
Identification of near zero variance predictors
resampleSummary
Summary of resampled performance estimates
varImp
Calculation of variable importance for regression and classification models
format.bagEarth
Format 'bagEarth' objects
sbf
Selection By Filtering (SBF)
caretFuncs
Backwards Feature Selection Helper Functions
trainControl
Control parameters for train
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
predict.knn3
Predictions from k-Nearest Neighbors
applyProcessing
Data Processing on Predictor Variables (Deprecated)
cars
Kelly Blue Book resale data for 2005 model year GM cars
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
as.table.confusionMatrix
Save Confusion Table Results
dotPlot
Create a dotplot of variable importance values
predictors
List predictors used in the model
print.train
Print Method for the train Class
plot.train
Plot Method for the train Class
knn3
k-Nearest Neighbour Classification
train
Fit Predictive Models over Different Tuning Parameters
pottery
Pottery from Pre-Classical Sites in Italy
BloodBrain
Blood Brain Barrier Data
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
spatialSign
Compute the multivariate spatial sign
plotClassProbs
Plot Predicted Probabilities in Classification Models
summary.bagEarth
Summarize a bagged earth or FDA fit