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caret (version 4.43)
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
163,965
Version
4.43
License
GPL-2
Maintainer
Max Kuhn
Last Published
July 1st, 2010
Functions in caret (4.43)
Search all functions
confusionMatrix
Create a confusion matrix
predict.bagEarth
Predicted values based on bagged Earth and FDA models
predictors
List predictors used in the model
resamples
Collation and Visualization of Resampling Results
as.table.confusionMatrix
Save Confusion Table Results
knnreg
k-Nearest Neighbour Regression
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
preProcess
Pre-Processing of Predictors
nullModel
Fit a simple, non-informative model
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
sbfControl
Control Object for Selection By Filtering (SBF)
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
classDist
Compute and predict the distances to class centroids
caretFuncs
Backwards Feature Selection Helper Functions
aucRoc
Compute the area under an ROC curve
pottery
Pottery from Pre-Classical Sites in Italy
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
spatialSign
Compute the multivariate spatial sign
caret-internal
Internal Functions
maxDissim
Maximum Dissimilarity Sampling
dhfr
Dihydrofolate Reductase Inhibitors Data
bagEarth
Bagged Earth
panel.needle
Needle Plot Lattice Panel
diff.resamples
Inferential Assessments About Model Performance
cox2
COX-2 Activity Data
nearZeroVar
Identification of near zero variance predictors
cars
Kelly Blue Book resale data for 2005 model year GM cars
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
postResample
Calculates performance across resamples
plotClassProbs
Plot Predicted Probabilities in Classification Models
resampleHist
Plot the resampling distribution of the model statistics
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
sbf
Selection By Filtering (SBF)
createGrid
Tuning Parameter Grid
applyProcessing
Data Processing on Predictor Variables (Deprecated)
predict.train
Extract predictions and class probabilities from train objects
histogram.train
Lattice functions for plotting resampling results
plot.varImp.train
Plotting variable importance measures
findLinearCombos
Determine linear combinations in a matrix
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
oil
Fatty acid composition of commercial oils
rfeControl
Controlling the Feature Selection Algorithms
resampleSummary
Summary of resampled performance estimates
createDataPartition
Data Splitting functions
dotPlot
Create a dotplot of variable importance values
oneSE
Selecting tuning Parameters
print.train
Print Method for the train Class
tecator
Fat, Water and Protein Content of Meat Samples
bagFDA
Bagged FDA
format.bagEarth
Format 'bagEarth' objects
print.confusionMatrix
Print method for confusionMatrix
train
Fit Predictive Models over Different Tuning Parameters
sensitivity
Calculate sensitivity, specificity and predictive values
summary.bagEarth
Summarize a bagged earth or FDA fit
icr.formula
Independent Component Regression
filterVarImp
Calculation of filter-based variable importance
pcaNNet.default
Neural Networks with a Principal Component Step
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
predict.knn3
Predictions from k-Nearest Neighbors
roc
Compute the points for an ROC curve
caretSBF
Selection By Filtering (SBF) Helper Functions
rfe
Backwards Feature Selection
BloodBrain
Blood Brain Barrier Data
findCorrelation
Determine highly correlated variables
knn3
k-Nearest Neighbour Classification
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
plot.train
Plot Method for the train Class
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
varImp
Calculation of variable importance for regression and classification models
trainControl
Control parameters for train