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caret (version 4.30)
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
231,168
Version
4.30
License
GPL-2
Maintainer
Max Kuhn
Last Published
November 9th, 2009
Functions in caret (4.30)
Search all functions
knnreg
k-Nearest Neighbour Regression
findLinearCombos
Determine linear combinations in a matrix
oil
Fatty acid composition of commercial oils
summary.bagEarth
Summarize a bagged earth or FDA fit
plot.train
Plot Method for the train Class
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
trainControl
Control parameters for train
tecator
Fat, Water and Protein Content of Maat Samples
predictors
List predictors used in the model
rfeControl
Controlling the Feature Selection Algorithms
spatialSign
Compute the multivariate spatial sign
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
panel.needle
Needle Plot Lattice Panel
predict.train
Extract predictions and class probabilities from train objects
plot.varImp.train
Plotting variable importance measures
pottery
Pottery from Pre-Classical Sites in Italy
preProcess
Pre-Processing of Predictors
print.confusionMatrix
Print method for confusionMatrix
nearZeroVar
Identification of near zero variance predictors
as.table.confusionMatrix
Save Confusion Table Results
confusionMatrix
Create a confusion matrix
classDist
Compute and predict the distances to class centroids
knn3
k-Nearest Neighbour Classification
applyProcessing
Data Processing on Predictor Variables (Deprecated)
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
bagEarth
Bagged Earth
createDataPartition
Data Splitting functions
aucRoc
Compute the area under an ROC curve
findCorrelation
Determine highly correlated variables
bagFDA
Bagged FDA
format.bagEarth
Format 'bagEarth' objects
dotPlot
Create a dotplot of variable importance values
cox2
COX-2 Activity Data
BloodBrain
Blood Brain Barrier Data
createGrid
Tuning Parameter Grid
filterVarImp
Calculation of filter-based variable importance
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
histogram.train
Lattice functions for plotting resampling results
maxDissim
Maximum Dissimilarity Sampling
caret-internal
Internal Functions
pcaNNet.default
Neural Networks with a Principal Component Step
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
plotClassProbs
Plot Predicted Probabilities in Classification Models
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
caretFuncs
Backwards Feature Selection Helper Functions
resampleSummary
Summary of resampled performance estimates
resampleHist
Plot the resampling distribution of the model statistics
predict.bagEarth
Predicted values based on bagged Earth and FDA models
train
Fit Predictive Models over Different Tuning Parameters
predict.knn3
Predictions from k-Nearest Neighbors
roc
Compute the points for an ROC curve
varImp
Calculation of variable importance for regression and classification models
sensitivity
Calculate sensitivity, specificity and predictive values
oneSE
Selecting tuning Parameters
print.train
Print Method for the train Class
postResample
Calculates performance across resamples
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
rfe
Backwards Feature Selection