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caret (version 4.17)
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
4.17
License
GPL-2
Maintainer
Max Kuhn
Last Published
June 5th, 2009
Functions in caret (4.17)
Search functions
predictors
List predictors used in the model
histogram.train
Lattice functions for plotting resampling results
confusionMatrix
Create a confusion matrix
findCorrelation
Determine highly correlated variables
preProcess
Pre-Processing of Predictors
caret-internal
Internal Functions
dotPlot
Create a dotplot of variable importance values
classDist
Compute and predict the distances to class centroids
bagEarth
Bagged Earth
bagFDA
Bagged FDA
cox2
COX-2 Activity Data
BloodBrain
Blood Brain Barrier Data
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
resampleSummary
Summary of resampled performance estimates
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
panel.needle
Needle Plot Lattice Panel
format.bagEarth
Format 'bagEarth' objects
predict.train
Extract predictions and class probabilities from train objects
findLinearCombos
Determine linear combinations in a matrix
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
maxDissim
Maximum Dissimilarity Sampling
pottery
Pottery from Pre-Classical Sites in Italy
plotClassProbs
Plot Predicted Probabilities in Classification Models
predict.bagEarth
Predicted values based on bagged Earth and FDA models
oil
Fatty acid composition of commercial oils
postResample
Calculates performance across resamples
createDataPartition
Data Splitting functions
rfeControl
Controlling the Feature Selection Algorithms
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
knnreg
k-Nearest Neighbour Regression
knn3
k-Nearest Neighbour Classification
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
createGrid
Tuning Parameter Grid
resampleHist
Plot the resampling distribution of the model statistics
plot.train
Plot Method for the train Class
pcaNNet.default
Neural Networks with a Principal Component Step
print.train
Print Method for the train Class
aucRoc
Compute the area under an ROC curve
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
plot.varImp.train
Plotting variable importance measures
tecator
Fat, Water and Protein Content of Maat Samples
predict.knn3
Predictions from k-Nearest Neighbors
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
varImp
Calculation of variable importance for regression and classification models
roc
Compute the points for an ROC curve
nearZeroVar
Identification of near zero variance predictors
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
applyProcessing
Data Processing on Predictor Variables (Deprecated)
spatialSign
Compute the multivariate spatial sign
filterVarImp
Calculation of filter-based variable importance
train
Fit Predictive Models over Different Tuning Parameters
sensitivity
Calculate sensitivity, specificity and predictive values
print.confusionMatrix
Print method for confusionMatrix
rfe
Backwards Feature Selection
as.table.confusionMatrix
Save Confusion Table Results
oneSE
Selecting tuning Parameters
trainControl
Control parameters for train
summary.bagEarth
Summarize a bagged earth or FDA fit