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caret (version 4.19)
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
4.19
License
GPL-2
Maintainer
Max Kuhn
Last Published
July 1st, 2009
Functions in caret (4.19)
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BloodBrain
Blood Brain Barrier Data
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
findCorrelation
Determine highly correlated variables
applyProcessing
Data Processing on Predictor Variables (Deprecated)
as.table.confusionMatrix
Save Confusion Table Results
confusionMatrix
Create a confusion matrix
knn3
k-Nearest Neighbour Classification
createDataPartition
Data Splitting functions
createGrid
Tuning Parameter Grid
bagFDA
Bagged FDA
classDist
Compute and predict the distances to class centroids
bagEarth
Bagged Earth
aucRoc
Compute the area under an ROC curve
cox2
COX-2 Activity Data
plot.varImp.train
Plotting variable importance measures
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
predict.train
Extract predictions and class probabilities from train objects
dotPlot
Create a dotplot of variable importance values
panel.needle
Needle Plot Lattice Panel
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
rfe
Backwards Feature Selection Helper Functions
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
maxDissim
Maximum Dissimilarity Sampling
pottery
Pottery from Pre-Classical Sites in Italy
caret-internal
Internal Functions
predict.knn3
Predictions from k-Nearest Neighbors
filterVarImp
Calculation of filter-based variable importance
trainControl
Control parameters for train
postResample
Calculates performance across resamples
histogram.train
Lattice functions for plotting resampling results
resampleSummary
Summary of resampled performance estimates
plot.train
Plot Method for the train Class
print.train
Print Method for the train Class
pcaNNet.default
Neural Networks with a Principal Component Step
tecator
Fat, Water and Protein Content of Maat Samples
predict.bagEarth
Predicted values based on bagged Earth and FDA models
findLinearCombos
Determine linear combinations in a matrix
print.confusionMatrix
Print method for confusionMatrix
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
nearZeroVar
Identification of near zero variance predictors
oil
Fatty acid composition of commercial oils
rfeControl
Controlling the Feature Selection Algorithms
roc
Compute the points for an ROC curve
knnreg
k-Nearest Neighbour Regression
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
predictors
List predictors used in the model
summary.bagEarth
Summarize a bagged earth or FDA fit
format.bagEarth
Format 'bagEarth' objects
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
preProcess
Pre-Processing of Predictors
plotClassProbs
Plot Predicted Probabilities in Classification Models
train
Fit Predictive Models over Different Tuning Parameters
oneSE
Selecting tuning Parameters
resampleHist
Plot the resampling distribution of the model statistics
spatialSign
Compute the multivariate spatial sign
sensitivity
Calculate sensitivity, specificity and predictive values
varImp
Calculation of variable importance for regression and classification models