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caret (version 4.11)
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
230,598
Version
4.11
License
GPL-2
Maintainer
Max Kuhn
Last Published
April 29th, 2009
Functions in caret (4.11)
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rfeControl
Controlling the Feature Selection Algorithms
plotClassProbs
Plot Predicted Probabilities in Classification Models
aucRoc
Compute the area under an ROC curve
createGrid
Tuning Parameter Grid
bagFDA
Bagged FDA
cox2
COX-2 Activity Data
bagEarth
Bagged Earth
pcaNNet.default
Neural Networks with a Principal Component Step
roc
Compute the points for an ROC curve
format.bagEarth
Format 'bagEarth' objects
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
as.table.confusionMatrix
Save Confusion Table Results
print.train
Print Method for the train Class
maxDissim
Maximum Dissimilarity Sampling
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
tecator
Fat, Water and Protein Content of Maat Samples
filterVarImp
Calculation of filter-based variable importance
postResample
Calculates performance across resamples
BloodBrain
Blood Brain Barrier Data
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
predict.knn3
Predictions from k-Nearest Neighbors
createDataPartition
Data Splitting functions
summary.bagEarth
Summarize a bagged earth or FDA fit
knn3
k-Nearest Neighbour Classification
oneSE
Selecting tuning Parameters
knnreg
k-Nearest Neighbour Regression
sensitivity
Calculate sensitivity, specificity and predictive values
pottery
Pottery from Pre-Classical Sites in Italy
predict.train
Extract predictions and class probabilities from train objects
findCorrelation
Determine highly correlated variables
plot.varImp.train
Plotting variable importance measures
panel.needle
Needle Plot Lattice Panel
trainControl
Control parameters for train
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
train
Fit Predictive Models over Different Tuning Parameters
resampleHist
Plot the resampling distribution of the model statistics
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
rfe
Backwards Feature Selection Helper Functions
nearZeroVar
Identification of near zero variance predictors
applyProcessing
Data Processing on Predictor Variables (Deprecated)
histogram.train
Lattice functions for plotting resampling results
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
predictors
List predictors used in the model
findLinearCombos
Determine linear combinations in a matrix
oil
Fatty acid composition of commercial oils
resampleSummary
Summary of resampled performance estimates
caret-internal
Internal Functions
dotPlot
Create a dotplot of variable importance values
preProcess
Pre-Processing of Predictors
confusionMatrix
Create a confusion matrix
spatialSign
Compute the multivariate spatial sign
varImp
Calculation of variable importance for regression and classification models
predict.bagEarth
Predicted values based on bagged Earth and FDA models
classDist
Compute and predict the distances to class centroids
print.confusionMatrix
Print method for confusionMatrix
plot.train
Plot Method for the train Class
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection