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caret (version 4.45)
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
231,168
Version
4.45
License
GPL-2
Maintainer
Max Kuhn
Last Published
July 28th, 2010
Functions in caret (4.45)
Search all functions
bagFDA
Bagged FDA
postResample
Calculates performance across resamples
pottery
Pottery from Pre-Classical Sites in Italy
applyProcessing
Data Processing on Predictor Variables (Deprecated)
as.table.confusionMatrix
Save Confusion Table Results
confusionMatrix
Create a confusion matrix
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
preProcess
Pre-Processing of Predictors
rfe
Backwards Feature Selection
predict.train
Extract predictions and class probabilities from train objects
trainControl
Control parameters for train
summary.bagEarth
Summarize a bagged earth or FDA fit
aucRoc
Compute the area under an ROC curve
cox2
COX-2 Activity Data
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
nearZeroVar
Identification of near zero variance predictors
resamples
Collation and Visualization of Resampling Results
BloodBrain
Blood Brain Barrier Data
tecator
Fat, Water and Protein Content of Meat Samples
caretSBF
Selection By Filtering (SBF) Helper Functions
bagEarth
Bagged Earth
plot.varImp.train
Plotting variable importance measures
nullModel
Fit a simple, non-informative model
predict.bagEarth
Predicted values based on bagged Earth and FDA models
roc
Compute the points for an ROC curve
sensitivity
Calculate sensitivity, specificity and predictive values
cars
Kelly Blue Book resale data for 2005 model year GM cars
varImp
Calculation of variable importance for regression and classification models
format.bagEarth
Format 'bagEarth' objects
oil
Fatty acid composition of commercial oils
print.train
Print Method for the train Class
print.confusionMatrix
Print method for confusionMatrix
bag.default
A General Framework For Bagging
createDataPartition
Data Splitting functions
dotPlot
Create a dotplot of variable importance values
knn3
k-Nearest Neighbour Classification
icr.formula
Independent Component Regression
maxDissim
Maximum Dissimilarity Sampling
findCorrelation
Determine highly correlated variables
dhfr
Dihydrofolate Reductase Inhibitors Data
sbfControl
Control Object for Selection By Filtering (SBF)
oneSE
Selecting tuning Parameters
spatialSign
Compute the multivariate spatial sign
diff.resamples
Inferential Assessments About Model Performance
plotClassProbs
Plot Predicted Probabilities in Classification Models
caret-internal
Internal Functions
panel.needle
Needle Plot Lattice Panel
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
predictors
List predictors used in the model
createGrid
Tuning Parameter Grid
predict.knn3
Predictions from k-Nearest Neighbors
plot.train
Plot Method for the train Class
findLinearCombos
Determine linear combinations in a matrix
resampleSummary
Summary of resampled performance estimates
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
caretFuncs
Backwards Feature Selection Helper Functions
sbf
Selection By Filtering (SBF)
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
train
Fit Predictive Models over Different Tuning Parameters
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
knnreg
k-Nearest Neighbour Regression
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
histogram.train
Lattice functions for plotting resampling results
filterVarImp
Calculation of filter-based variable importance
pcaNNet.default
Neural Networks with a Principal Component Step
resampleHist
Plot the resampling distribution of the model statistics
rfeControl
Controlling the Feature Selection Algorithms
classDist
Compute and predict the distances to class centroids