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caret (version 4.24)
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
185,160
Version
4.24
License
GPL-2
Maintainer
Max Kuhn
Last Published
September 30th, 2009
Functions in caret (4.24)
Search functions
BloodBrain
Blood Brain Barrier Data
as.table.confusionMatrix
Save Confusion Table Results
panel.needle
Needle Plot Lattice Panel
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
format.bagEarth
Format 'bagEarth' objects
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
pcaNNet.default
Neural Networks with a Principal Component Step
print.confusionMatrix
Print method for confusionMatrix
knn3
k-Nearest Neighbour Classification
predict.train
Extract predictions and class probabilities from train objects
caret-internal
Internal Functions
oil
Fatty acid composition of commercial oils
plot.train
Plot Method for the train Class
maxDissim
Maximum Dissimilarity Sampling
predict.bagEarth
Predicted values based on bagged Earth and FDA models
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
createGrid
Tuning Parameter Grid
applyProcessing
Data Processing on Predictor Variables (Deprecated)
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
knnreg
k-Nearest Neighbour Regression
plot.varImp.train
Plotting variable importance measures
findLinearCombos
Determine linear combinations in a matrix
findCorrelation
Determine highly correlated variables
resampleHist
Plot the resampling distribution of the model statistics
nearZeroVar
Identification of near zero variance predictors
oneSE
Selecting tuning Parameters
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
filterVarImp
Calculation of filter-based variable importance
confusionMatrix
Create a confusion matrix
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
rfe
Backwards Feature Selection
rfeControl
Controlling the Feature Selection Algorithms
createDataPartition
Data Splitting functions
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
predictors
List predictors used in the model
spatialSign
Compute the multivariate spatial sign
sensitivity
Calculate sensitivity, specificity and predictive values
histogram.train
Lattice functions for plotting resampling results
plotClassProbs
Plot Predicted Probabilities in Classification Models
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
pottery
Pottery from Pre-Classical Sites in Italy
varImp
Calculation of variable importance for regression and classification models
bagFDA
Bagged FDA
predict.knn3
Predictions from k-Nearest Neighbors
classDist
Compute and predict the distances to class centroids
trainControl
Control parameters for train
train
Fit Predictive Models over Different Tuning Parameters
bagEarth
Bagged Earth
roc
Compute the points for an ROC curve
dotPlot
Create a dotplot of variable importance values
print.train
Print Method for the train Class
caretFuncs
Backwards Feature Selection Helper Functions
resampleSummary
Summary of resampled performance estimates
tecator
Fat, Water and Protein Content of Maat Samples
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
postResample
Calculates performance across resamples
aucRoc
Compute the area under an ROC curve
cox2
COX-2 Activity Data
summary.bagEarth
Summarize a bagged earth or FDA fit
preProcess
Pre-Processing of Predictors