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caret (version 4.77)
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
160,352
Version
4.77
License
GPL-2
Maintainer
Max Kuhn
Last Published
January 23rd, 2011
Functions in caret (4.77)
Search functions
filterVarImp
Calculation of filter-based variable importance
knnreg
k-Nearest Neighbour Regression
rfeControl
Controlling the Feature Selection Algorithms
findLinearCombos
Determine linear combinations in a matrix
aucRoc
Compute the area under an ROC curve
nullModel
Fit a simple, non-informative model
applyProcessing
Data Processing on Predictor Variables (Deprecated)
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
dotPlot
Create a dotplot of variable importance values
sbf
Selection By Filtering (SBF)
bagFDA
Bagged FDA
icr.formula
Independent Component Regression
format.bagEarth
Format 'bagEarth' objects
knn3
k-Nearest Neighbour Classification
predict.train
Extract predictions and class probabilities from train objects
findCorrelation
Determine highly correlated variables
predict.knn3
Predictions from k-Nearest Neighbors
tecator
Fat, Water and Protein Content of Meat Samples
resampleSummary
Summary of resampled performance estimates
resamples
Collation and Visualization of Resampling Results
oneSE
Selecting tuning Parameters
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
dummyVars
Create A Full Set of Dummy Variables
bag.default
A General Framework For Bagging
roc
Compute the points for an ROC curve
BloodBrain
Blood Brain Barrier Data
segmentationData
Cell Body Segmentation
spatialSign
Compute the multivariate spatial sign
classDist
Compute and predict the distances to class centroids
plot.varImp.train
Plotting variable importance measures
predict.bagEarth
Predicted values based on bagged Earth and FDA models
caretSBF
Selection By Filtering (SBF) Helper Functions
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
createDataPartition
Data Splitting functions
rfe
Backwards Feature Selection
print.confusionMatrix
Print method for confusionMatrix
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
BoxCoxTrans.default
Box-Cox Transformations
resampleHist
Plot the resampling distribution of the model statistics
sensitivity
Calculate sensitivity, specificity and predictive values
maxDissim
Maximum Dissimilarity Sampling
plotClassProbs
Plot Predicted Probabilities in Classification Models
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
bagEarth
Bagged Earth
summary.bagEarth
Summarize a bagged earth or FDA fit
print.train
Print Method for the train Class
diff.resamples
Inferential Assessments About Model Performance
as.table.confusionMatrix
Save Confusion Table Results
caret-internal
Internal Functions
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
prcomp.resamples
Principal Components Analysis of Resampling Results
dhfr
Dihydrofolate Reductase Inhibitors Data
nearZeroVar
Identification of near zero variance predictors
plot.train
Plot Method for the train Class
cars
Kelly Blue Book resale data for 2005 model year GM cars
GermanCredit
German Credit Data
confusionMatrix
Create a confusion matrix
postResample
Calculates performance across resamples
histogram.train
Lattice functions for plotting resampling results
predictors
List predictors used in the model
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
panel.needle
Needle Plot Lattice Panel
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
oil
Fatty acid composition of commercial oils
pcaNNet.default
Neural Networks with a Principal Component Step
modelLookup
Descriptions Of Models Available in train()
train
Fit Predictive Models over Different Tuning Parameters
pottery
Pottery from Pre-Classical Sites in Italy
sbfControl
Control Object for Selection By Filtering (SBF)
createGrid
Tuning Parameter Grid
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
preProcess
Pre-Processing of Predictors
caretFuncs
Backwards Feature Selection Helper Functions
varImp
Calculation of variable importance for regression and classification models
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
cox2
COX-2 Activity Data
trainControl
Control parameters for train