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caret (version 4.16)
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
4.16
License
GPL-2
Maintainer
Max Kuhn
Last Published
May 24th, 2009
Functions in caret (4.16)
Search functions
aucRoc
Compute the area under an ROC curve
maxDissim
Maximum Dissimilarity Sampling
summary.bagEarth
Summarize a bagged earth or FDA fit
confusionMatrix
Create a confusion matrix
panel.needle
Needle Plot Lattice Panel
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
rfe
Backwards Feature Selection Helper Functions
varImp
Calculation of variable importance for regression and classification models
dotPlot
Create a dotplot of variable importance values
filterVarImp
Calculation of filter-based variable importance
plotClassProbs
Plot Predicted Probabilities in Classification Models
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
preProcess
Pre-Processing of Predictors
pottery
Pottery from Pre-Classical Sites in Italy
plot.train
Plot Method for the train Class
predict.knn3
Predictions from k-Nearest Neighbors
predict.train
Extract predictions and class probabilities from train objects
oil
Fatty acid composition of commercial oils
print.train
Print Method for the train Class
histogram.train
Lattice functions for plotting resampling results
oneSE
Selecting tuning Parameters
findCorrelation
Determine highly correlated variables
createDataPartition
Data Splitting functions
applyProcessing
Data Processing on Predictor Variables (Deprecated)
cox2
COX-2 Activity Data
plot.varImp.train
Plotting variable importance measures
format.bagEarth
Format 'bagEarth' objects
as.table.confusionMatrix
Save Confusion Table Results
rfeControl
Controlling the Feature Selection Algorithms
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
resampleSummary
Summary of resampled performance estimates
createGrid
Tuning Parameter Grid
resampleHist
Plot the resampling distribution of the model statistics
postResample
Calculates performance across resamples
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
caret-internal
Internal Functions
print.confusionMatrix
Print method for confusionMatrix
tecator
Fat, Water and Protein Content of Maat Samples
sensitivity
Calculate sensitivity, specificity and predictive values
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
findLinearCombos
Determine linear combinations in a matrix
spatialSign
Compute the multivariate spatial sign
pcaNNet.default
Neural Networks with a Principal Component Step
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
knn3
k-Nearest Neighbour Classification
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
predictors
List predictors used in the model
bagEarth
Bagged Earth
predict.bagEarth
Predicted values based on bagged Earth and FDA models
knnreg
k-Nearest Neighbour Regression
nearZeroVar
Identification of near zero variance predictors
trainControl
Control parameters for train
roc
Compute the points for an ROC curve
BloodBrain
Blood Brain Barrier Data
bagFDA
Bagged FDA
train
Fit Predictive Models over Different Tuning Parameters
classDist
Compute and predict the distances to class centroids