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caret (version 5.12-04)
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
222,842
Version
5.12-04
License
GPL-2
Maintainer
Max Kuhn
Last Published
January 15th, 2012
Functions in caret (5.12-04)
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summary.bagEarth
Summarize a bagged earth or FDA fit
pcaNNet.default
Neural Networks with a Principal Component Step
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
spatialSign
Compute the multivariate spatial sign
format.bagEarth
Format 'bagEarth' objects
GermanCredit
German Credit Data
cars
Kelly Blue Book resale data for 2005 model year GM cars
classDist
Compute and predict the distances to class centroids
BoxCoxTrans.default
Box-Cox Transformations
aucRoc
Compute the area under an ROC curve
diff.resamples
Inferential Assessments About Model Performance
cox2
COX-2 Activity Data
createDataPartition
Data Splitting functions
createGrid
Tuning Parameter Grid
dummyVars
Create A Full Set of Dummy Variables
findCorrelation
Determine highly correlated variables
bag.default
A General Framework For Bagging
predict.train
Extract predictions and class probabilities from train objects
confusionMatrix.train
Estimate a Resampled Confusion Matrix
dotPlot
Create a dotplot of variable importance values
histogram.train
Lattice functions for plotting resampling results
icr.formula
Independent Component Regression
findLinearCombos
Determine linear combinations in a matrix
avNNet.default
Neural Networks Using Model Averaging
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
as.table.confusionMatrix
Save Confusion Table Results
print.confusionMatrix
Print method for confusionMatrix
caretSBF
Selection By Filtering (SBF) Helper Functions
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
modelLookup
Descriptions Of Models Available in train()
nullModel
Fit a simple, non-informative model
plot.train
Plot Method for the train Class
knn3
k-Nearest Neighbour Classification
nearZeroVar
Identification of near zero variance predictors
resampleHist
Plot the resampling distribution of the model statistics
prcomp.resamples
Principal Components Analysis of Resampling Results
trainControl
Control parameters for train
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
postResample
Calculates performance across resamples
rfe
Backwards Feature Selection
panel.lift2
Lattice Panel Functions for Lift Plots
caretFuncs
Backwards Feature Selection Helper Functions
caret-internal
Internal Functions
predict.bagEarth
Predicted values based on bagged Earth and FDA models
sbf
Selection By Filtering (SBF)
rfeControl
Controlling the Feature Selection Algorithms
segmentationData
Cell Body Segmentation
resampleSummary
Summary of resampled performance estimates
varImp
Calculation of variable importance for regression and classification models
sensitivity
Calculate sensitivity, specificity and predictive values
train
Fit Predictive Models over Different Tuning Parameters
resamples
Collation and Visualization of Resampling Results
oil
Fatty acid composition of commercial oils
maxDissim
Maximum Dissimilarity Sampling
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
preProcess
Pre-Processing of Predictors
confusionMatrix
Create a confusion matrix
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
knnreg
k-Nearest Neighbour Regression
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
sbfControl
Control Object for Selection By Filtering (SBF)
oneSE
Selecting tuning Parameters
panel.needle
Needle Plot Lattice Panel
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
lift
Lift Plot
predict.knn3
Predictions from k-Nearest Neighbors
tecator
Fat, Water and Protein Content of Meat Samples
BloodBrain
Blood Brain Barrier Data
bagFDA
Bagged FDA
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
plot.varImp.train
Plotting variable importance measures
pottery
Pottery from Pre-Classical Sites in Italy
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
predictors
List predictors used in the model
roc
Compute the points for an ROC curve
dhfr
Dihydrofolate Reductase Inhibitors Data
bagEarth
Bagged Earth
plotClassProbs
Plot Predicted Probabilities in Classification Models
print.train
Print Method for the train Class
filterVarImp
Calculation of filter-based variable importance