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caret (version 4.10)
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
4.10
License
GPL-2
Maintainer
Max Kuhn
Last Published
March 27th, 2009
Functions in caret (4.10)
Search all functions
format.bagEarth
Format 'bagEarth' objects
pottery
Pottery from Pre-Classical Sites in Italy
confusionMatrix
Create a confusion matrix
predict.bagEarth
Predicted values based on bagged Earth and FDA models
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
predictors
List predictors used in the model
roc
Compute the points for an ROC curve
applyProcessing
Data Processing on Predictor Variables (Deprecated)
dotPlot
Create a dotplot of variable importance values
findCorrelation
Determine highly correlated variables
caret-internal
Internal Functions
plot.varImp.train
Plotting variable importance measures
predict.train
Extract predictions and class probabilities from train objects
print.confusionMatrix
Print method for confusionMatrix
bagFDA
Bagged FDA
nearZeroVar
Identification of near zero variance predictors
bagEarth
Bagged Earth
oil
Fatty acid composition of commercial oils
createGrid
Tuning Parameter Grid
trainControl
Control parameters for train
histogram.train
Lattice functions for plotting resampling results
preProcess
Pre-Processing of Predictors
cox2
COX-2 Activity Data
BloodBrain
Blood Brain Barrier Data
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
aucRoc
Compute the area under an ROC curve
varImp
Calculation of variable importance for regression and classification models
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
createDataPartition
Data Splitting functions
as.table.confusionMatrix
Save Confusion Table Results
sensitivity
Calculate sensitivity, specificity and predictive values
resampleHist
Plot the resampling distribution of the model statistics
print.train
Print Method for the train Class
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
resampleSummary
Summary of resampled performance estimates
maxDissim
Maximum Dissimilarity Sampling
spatialSign
Compute the multivariate spatial sign
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
summary.bagEarth
Summarize a bagged earth or FDA fit
train
Fit Predictive Models over Different Tuning Parameters
plotClassProbs
Plot Predicted Probabilities in Classification Models
predict.knn3
Predictions from k-Nearest Neighbors
postResample
Calculates performance across resamples
findLinearCombos
Determine linear combinations in a matrix
oneSE
Selecting tuning Parameters
filterVarImp
Calculation of filter-based variable importance
panel.needle
Needle Plot Lattice Panel
plot.train
Plot Method for the train Class
pcaNNet.default
Neural Networks with a Principal Component Step
knn3
k-Nearest Neighbour Classification
tecator
Fat, Water and Protein Content of Maat Samples