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caret (version 4.53)
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
158,845
Version
4.53
License
GPL-2
Maintainer
Max Kuhn
Last Published
August 17th, 2010
Functions in caret (4.53)
Search all functions
predict.train
Extract predictions and class probabilities from train objects
nullModel
Fit a simple, non-informative model
dhfr
Dihydrofolate Reductase Inhibitors Data
predict.knn3
Predictions from k-Nearest Neighbors
knnreg
k-Nearest Neighbour Regression
as.table.confusionMatrix
Save Confusion Table Results
bagFDA
Bagged FDA
caretSBF
Selection By Filtering (SBF) Helper Functions
GermanCredit
German Credit Data
predict.bagEarth
Predicted values based on bagged Earth and FDA models
filterVarImp
Calculation of filter-based variable importance
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
prcomp.resamples
Principal Components Analysis of Resampling Results
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
createDataPartition
Data Splitting functions
resampleHist
Plot the resampling distribution of the model statistics
dotPlot
Create a dotplot of variable importance values
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
maxDissim
Maximum Dissimilarity Sampling
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
sbf
Selection By Filtering (SBF)
preProcess
Pre-Processing of Predictors
nearZeroVar
Identification of near zero variance predictors
panel.needle
Needle Plot Lattice Panel
rfe
Backwards Feature Selection
BloodBrain
Blood Brain Barrier Data
caretFuncs
Backwards Feature Selection Helper Functions
resamples
Collation and Visualization of Resampling Results
tecator
Fat, Water and Protein Content of Meat Samples
cox2
COX-2 Activity Data
bagEarth
Bagged Earth
postResample
Calculates performance across resamples
bag.default
A General Framework For Bagging
createGrid
Tuning Parameter Grid
resampleSummary
Summary of resampled performance estimates
caret-internal
Internal Functions
plot.train
Plot Method for the train Class
findLinearCombos
Determine linear combinations in a matrix
classDist
Compute and predict the distances to class centroids
knn3
k-Nearest Neighbour Classification
predictors
List predictors used in the model
oneSE
Selecting tuning Parameters
diff.resamples
Inferential Assessments About Model Performance
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
sensitivity
Calculate sensitivity, specificity and predictive values
icr.formula
Independent Component Regression
plot.varImp.train
Plotting variable importance measures
oil
Fatty acid composition of commercial oils
varImp
Calculation of variable importance for regression and classification models
print.train
Print Method for the train Class
sbfControl
Control Object for Selection By Filtering (SBF)
spatialSign
Compute the multivariate spatial sign
print.confusionMatrix
Print method for confusionMatrix
findCorrelation
Determine highly correlated variables
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
applyProcessing
Data Processing on Predictor Variables (Deprecated)
train
Fit Predictive Models over Different Tuning Parameters
cars
Kelly Blue Book resale data for 2005 model year GM cars
roc
Compute the points for an ROC curve
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
rfeControl
Controlling the Feature Selection Algorithms
summary.bagEarth
Summarize a bagged earth or FDA fit
trainControl
Control parameters for train
confusionMatrix
Create a confusion matrix
aucRoc
Compute the area under an ROC curve
format.bagEarth
Format 'bagEarth' objects
histogram.train
Lattice functions for plotting resampling results
pcaNNet.default
Neural Networks with a Principal Component Step
pottery
Pottery from Pre-Classical Sites in Italy
plotClassProbs
Plot Predicted Probabilities in Classification Models