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caret (version 4.26)
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
138,220
Version
4.26
License
GPL-2
Maintainer
Max Kuhn
Last Published
October 28th, 2009
Functions in caret (4.26)
Search all functions
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
bagFDA
Bagged FDA
plotClassProbs
Plot Predicted Probabilities in Classification Models
as.table.confusionMatrix
Save Confusion Table Results
filterVarImp
Calculation of filter-based variable importance
caretFuncs
Backwards Feature Selection Helper Functions
predict.bagEarth
Predicted values based on bagged Earth and FDA models
histogram.train
Lattice functions for plotting resampling results
maxDissim
Maximum Dissimilarity Sampling
bagEarth
Bagged Earth
print.train
Print Method for the train Class
findLinearCombos
Determine linear combinations in a matrix
roc
Compute the points for an ROC curve
cox2
COX-2 Activity Data
rfeControl
Controlling the Feature Selection Algorithms
findCorrelation
Determine highly correlated variables
applyProcessing
Data Processing on Predictor Variables (Deprecated)
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
format.bagEarth
Format 'bagEarth' objects
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
createDataPartition
Data Splitting functions
predictors
List predictors used in the model
createGrid
Tuning Parameter Grid
resampleHist
Plot the resampling distribution of the model statistics
summary.bagEarth
Summarize a bagged earth or FDA fit
dotPlot
Create a dotplot of variable importance values
pcaNNet.default
Neural Networks with a Principal Component Step
knn3
k-Nearest Neighbour Classification
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
panel.needle
Needle Plot Lattice Panel
pottery
Pottery from Pre-Classical Sites in Italy
classDist
Compute and predict the distances to class centroids
BloodBrain
Blood Brain Barrier Data
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
aucRoc
Compute the area under an ROC curve
tecator
Fat, Water and Protein Content of Maat Samples
confusionMatrix
Create a confusion matrix
train
Fit Predictive Models over Different Tuning Parameters
knnreg
k-Nearest Neighbour Regression
nearZeroVar
Identification of near zero variance predictors
predict.train
Extract predictions and class probabilities from train objects
print.confusionMatrix
Print method for confusionMatrix
caret-internal
Internal Functions
oil
Fatty acid composition of commercial oils
varImp
Calculation of variable importance for regression and classification models
plot.train
Plot Method for the train Class
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
oneSE
Selecting tuning Parameters
resampleSummary
Summary of resampled performance estimates
trainControl
Control parameters for train
postResample
Calculates performance across resamples
sensitivity
Calculate sensitivity, specificity and predictive values
preProcess
Pre-Processing of Predictors
predict.knn3
Predictions from k-Nearest Neighbors
rfe
Backwards Feature Selection
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
plot.varImp.train
Plotting variable importance measures
spatialSign
Compute the multivariate spatial sign