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caret (version 4.20)
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
4.20
License
GPL-2
Maintainer
Max Kuhn
Last Published
August 25th, 2009
Functions in caret (4.20)
Search all functions
confusionMatrix
Create a confusion matrix
bagFDA
Bagged FDA
resampleHist
Plot the resampling distribution of the model statistics
pottery
Pottery from Pre-Classical Sites in Italy
print.confusionMatrix
Print method for confusionMatrix
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
classDist
Compute and predict the distances to class centroids
spatialSign
Compute the multivariate spatial sign
maxDissim
Maximum Dissimilarity Sampling
trainControl
Control parameters for train
predict.train
Extract predictions and class probabilities from train objects
as.table.confusionMatrix
Save Confusion Table Results
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
filterVarImp
Calculation of filter-based variable importance
aucRoc
Compute the area under an ROC curve
preProcess
Pre-Processing of Predictors
bagEarth
Bagged Earth
sensitivity
Calculate sensitivity, specificity and predictive values
plotClassProbs
Plot Predicted Probabilities in Classification Models
roc
Compute the points for an ROC curve
panel.needle
Needle Plot Lattice Panel
nearZeroVar
Identification of near zero variance predictors
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
histogram.train
Lattice functions for plotting resampling results
knn3
k-Nearest Neighbour Classification
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
pcaNNet.default
Neural Networks with a Principal Component Step
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
createDataPartition
Data Splitting functions
dotPlot
Create a dotplot of variable importance values
resampleSummary
Summary of resampled performance estimates
rfe
Backwards Feature Selection Helper Functions
predict.knn3
Predictions from k-Nearest Neighbors
oneSE
Selecting tuning Parameters
predict.bagEarth
Predicted values based on bagged Earth and FDA models
cox2
COX-2 Activity Data
varImp
Calculation of variable importance for regression and classification models
format.bagEarth
Format 'bagEarth' objects
plot.train
Plot Method for the train Class
createGrid
Tuning Parameter Grid
knnreg
k-Nearest Neighbour Regression
findLinearCombos
Determine linear combinations in a matrix
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
print.train
Print Method for the train Class
summary.bagEarth
Summarize a bagged earth or FDA fit
tecator
Fat, Water and Protein Content of Maat Samples
caret-internal
Internal Functions
plot.varImp.train
Plotting variable importance measures
train
Fit Predictive Models over Different Tuning Parameters
findCorrelation
Determine highly correlated variables
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
rfeControl
Controlling the Feature Selection Algorithms
applyProcessing
Data Processing on Predictor Variables (Deprecated)
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
BloodBrain
Blood Brain Barrier Data
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
predictors
List predictors used in the model
postResample
Calculates performance across resamples
oil
Fatty acid composition of commercial oils