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caret (version 3.37)
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
3.37
License
GPL-2
Maintainer
Max Kuhn
Last Published
September 4th, 2008
Functions in caret (3.37)
Search functions
caret-internal
Internal Functions
nearZeroVar
Identification of near zero variance predictors
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
createDataPartition
Data Splitting functions
BloodBrain
Blood Brain Barrier Data
plsda
Partial Least Squares Discriminant Analysis
aucRoc
Compute the area under an ROC curve
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
panel.needle
Needle Plot Lattice Panel
predict.train
Extract predictions and class probabilities from train objects
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
plotClassProbs
Plot Predicted Probabilities in Classification Models
findLinearCombos
Determine linear combinations in a matrix
filterVarImp
Calculation of filter-based variable importance
plot.varImp.train
Plotting variable importance measures
maxDissim
Maximum Dissimilarity Sampling
sensitivity
Calculate Sensitivity, Specificity and predictive values
findCorrelation
Determine highly correlated variables
varImp
Calculation of variable importance for regression and classification models
spatialSign
Compute the multivariate spatial sign
summary.bagEarth
Summarize a bagged earth or FDA fit
preProcess
Pre-Processing of Predictors
plot.train
Plot Method for the train Class
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
oneSE
Selecting tuning Parameters
bagEarth
Bagged Earth
resampleHist
Plot the resampling distribution of the model statistics
print.train
Print Method for the train Class
train
Fit Predictive Models over Different Tuning Parameters
pottery
Pottery from Pre-Classical Sites in Italy
pcaNNet.default
Neural Networks with a Principal Component Step
resampleSummary
Summary of resampled performance estimates
trainControl
Control parameters for train
roc
Compute the points for an ROC curve
dotPlot
Create a dotplot of variable importance values
bagFDA
Bagged FDA
cox2
COX-2 Activity Data
oil
Fatty acid composition of commercial oils
predict.knn3
Predictions from k-Nearest Neighbors
postResample
Calculates performance across resamples
createGrid
Tuning Parameter Grid
confusionMatrix
Create a confusion matrix
knn3
k-Nearest Neighbour Classification
tecator
Fat, Water and Protein Content of Maat Samples
print.confusionMatrix
Print method for confusionMatrix
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
format.bagEarth
Format 'bagEarth' objects
applyProcessing
Data Processing on Predictor Variables (Deprecated)
predict.bagEarth
Predicted values based on bagged Earth and FDA models
histogram.train
Lattice functions for plotting resampling results
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution