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caret (version 4.34)
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
158,845
Version
4.34
License
GPL-2
Maintainer
Max Kuhn
Last Published
March 18th, 2010
Functions in caret (4.34)
Search all functions
bagFDA
Bagged FDA
bagEarth
Bagged Earth
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
filterVarImp
Calculation of filter-based variable importance
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
panel.needle
Needle Plot Lattice Panel
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
dotPlot
Create a dotplot of variable importance values
print.train
Print Method for the train Class
oil
Fatty acid composition of commercial oils
nullModel
Fit a simple, non-informative model
nearZeroVar
Identification of near zero variance predictors
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
roc
Compute the points for an ROC curve
applyProcessing
Data Processing on Predictor Variables (Deprecated)
aucRoc
Compute the area under an ROC curve
findCorrelation
Determine highly correlated variables
rfe
Backwards Feature Selection
sbf
Selection By Filtering (SBF)
findLinearCombos
Determine linear combinations in a matrix
predict.bagEarth
Predicted values based on bagged Earth and FDA models
rfeControl
Controlling the Feature Selection Algorithms
varImp
Calculation of variable importance for regression and classification models
postResample
Calculates performance across resamples
pottery
Pottery from Pre-Classical Sites in Italy
spatialSign
Compute the multivariate spatial sign
caretSBF
Selection By Filtering (SBF) Helper Functions
caret-internal
Internal Functions
createGrid
Tuning Parameter Grid
confusionMatrix
Create a confusion matrix
plot.train
Plot Method for the train Class
maxDissim
Maximum Dissimilarity Sampling
plotClassProbs
Plot Predicted Probabilities in Classification Models
dhfr
Dihydrofolate Reductase Inhibitors Data
createDataPartition
Data Splitting functions
sbfControl
Control Object for Selection By Filtering (SBF)
resampleHist
Plot the resampling distribution of the model statistics
knnreg
k-Nearest Neighbour Regression
trainControl
Control parameters for train
resampleSummary
Summary of resampled performance estimates
sensitivity
Calculate sensitivity, specificity and predictive values
tecator
Fat, Water and Protein Content of Maat Samples
summary.bagEarth
Summarize a bagged earth or FDA fit
predictors
List predictors used in the model
knn3
k-Nearest Neighbour Classification
cars
Kelly Blue Book resale data for 2005 model year GM cars
classDist
Compute and predict the distances to class centroids
predict.train
Extract predictions and class probabilities from train objects
histogram.train
Lattice functions for plotting resampling results
pcaNNet.default
Neural Networks with a Principal Component Step
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
preProcess
Pre-Processing of Predictors
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
predict.knn3
Predictions from k-Nearest Neighbors
as.table.confusionMatrix
Save Confusion Table Results
format.bagEarth
Format 'bagEarth' objects
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
oneSE
Selecting tuning Parameters
caretFuncs
Backwards Feature Selection Helper Functions
BloodBrain
Blood Brain Barrier Data
cox2
COX-2 Activity Data
plot.varImp.train
Plotting variable importance measures
print.confusionMatrix
Print method for confusionMatrix
train
Fit Predictive Models over Different Tuning Parameters