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caret (version 5.11-06)
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
5.11-06
License
GPL-2
Maintainer
Max Kuhn
Last Published
January 13th, 2012
Functions in caret (5.11-06)
Search functions
confusionMatrix.train
Estimate a Resampled Confusion Matrix
classDist
Compute and predict the distances to class centroids
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
findLinearCombos
Determine linear combinations in a matrix
dhfr
Dihydrofolate Reductase Inhibitors Data
BloodBrain
Blood Brain Barrier Data
bag.default
A General Framework For Bagging
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
lift
Lift Plot
histogram.train
Lattice functions for plotting resampling results
knnreg
k-Nearest Neighbour Regression
BoxCoxTrans.default
Box-Cox Transformations
postResample
Calculates performance across resamples
panel.needle
Needle Plot Lattice Panel
plot.varImp.train
Plotting variable importance measures
createGrid
Tuning Parameter Grid
spatialSign
Compute the multivariate spatial sign
predict.train
Extract predictions and class probabilities from train objects
train
Fit Predictive Models over Different Tuning Parameters
plotClassProbs
Plot Predicted Probabilities in Classification Models
pcaNNet.default
Neural Networks with a Principal Component Step
confusionMatrix
Create a confusion matrix
caret-internal
Internal Functions
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
caretSBF
Selection By Filtering (SBF) Helper Functions
summary.bagEarth
Summarize a bagged earth or FDA fit
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
createDataPartition
Data Splitting functions
avNNet.default
Neural Networks Using Model Averaging
dotPlot
Create a dotplot of variable importance values
sbfControl
Control Object for Selection By Filtering (SBF)
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
dummyVars
Create A Full Set of Dummy Variables
plot.train
Plot Method for the train Class
varImp
Calculation of variable importance for regression and classification models
diff.resamples
Inferential Assessments About Model Performance
nullModel
Fit a simple, non-informative model
caretFuncs
Backwards Feature Selection Helper Functions
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
predict.bagEarth
Predicted values based on bagged Earth and FDA models
rfeControl
Controlling the Feature Selection Algorithms
resamples
Collation and Visualization of Resampling Results
sbf
Selection By Filtering (SBF)
print.train
Print Method for the train Class
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
segmentationData
Cell Body Segmentation
resampleSummary
Summary of resampled performance estimates
tecator
Fat, Water and Protein Content of Meat Samples
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
maxDissim
Maximum Dissimilarity Sampling
predictors
List predictors used in the model
roc
Compute the points for an ROC curve
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
trainControl
Control parameters for train
as.table.confusionMatrix
Save Confusion Table Results
bagEarth
Bagged Earth
format.bagEarth
Format 'bagEarth' objects
prcomp.resamples
Principal Components Analysis of Resampling Results
GermanCredit
German Credit Data
preProcess
Pre-Processing of Predictors
bagFDA
Bagged FDA
sensitivity
Calculate sensitivity, specificity and predictive values
cars
Kelly Blue Book resale data for 2005 model year GM cars
filterVarImp
Calculation of filter-based variable importance
icr.formula
Independent Component Regression
panel.lift2
Lattice Panel Functions for Lift Plots
pottery
Pottery from Pre-Classical Sites in Italy
print.confusionMatrix
Print method for confusionMatrix
oneSE
Selecting tuning Parameters
rfe
Backwards Feature Selection
findCorrelation
Determine highly correlated variables
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
predict.knn3
Predictions from k-Nearest Neighbors
knn3
k-Nearest Neighbour Classification
oil
Fatty acid composition of commercial oils
aucRoc
Compute the area under an ROC curve
nearZeroVar
Identification of near zero variance predictors
resampleHist
Plot the resampling distribution of the model statistics
cox2
COX-2 Activity Data
modelLookup
Descriptions Of Models Available in train()