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caret (version 4.15)
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
4.15
License
GPL-2
Maintainer
Max Kuhn
Last Published
May 13th, 2009
Functions in caret (4.15)
Search all functions
cox2
COX-2 Activity Data
format.bagEarth
Format 'bagEarth' objects
sensitivity
Calculate sensitivity, specificity and predictive values
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
oil
Fatty acid composition of commercial oils
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
createDataPartition
Data Splitting functions
aucRoc
Compute the area under an ROC curve
predict.bagEarth
Predicted values based on bagged Earth and FDA models
bagFDA
Bagged FDA
createGrid
Tuning Parameter Grid
filterVarImp
Calculation of filter-based variable importance
resampleSummary
Summary of resampled performance estimates
caret-internal
Internal Functions
BloodBrain
Blood Brain Barrier Data
tecator
Fat, Water and Protein Content of Maat Samples
predict.train
Extract predictions and class probabilities from train objects
nearZeroVar
Identification of near zero variance predictors
trainControl
Control parameters for train
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
print.train
Print Method for the train Class
histogram.train
Lattice functions for plotting resampling results
knnreg
k-Nearest Neighbour Regression
confusionMatrix
Create a confusion matrix
pottery
Pottery from Pre-Classical Sites in Italy
rfe
Backwards Feature Selection
classDist
Compute and predict the distances to class centroids
dotPlot
Create a dotplot of variable importance values
plot.varImp.train
Plotting variable importance measures
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
summary.bagEarth
Summarize a bagged earth or FDA fit
findCorrelation
Determine highly correlated variables
pcaNNet.default
Neural Networks with a Principal Component Step
plot.train
Plot Method for the train Class
varImp
Calculation of variable importance for regression and classification models
postResample
Calculates performance across resamples
rfeControl
Controlling the Feature Selection Algorithms
resampleHist
Plot the resampling distribution of the model statistics
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
maxDissim
Maximum Dissimilarity Sampling
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
roc
Compute the points for an ROC curve
bagEarth
Bagged Earth
spatialSign
Compute the multivariate spatial sign
preProcess
Pre-Processing of Predictors
oneSE
Selecting tuning Parameters
panel.needle
Needle Plot Lattice Panel
predict.knn3
Predictions from k-Nearest Neighbors
train
Fit Predictive Models over Different Tuning Parameters
print.confusionMatrix
Print method for confusionMatrix
findLinearCombos
Determine linear combinations in a matrix
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
plotClassProbs
Plot Predicted Probabilities in Classification Models
knn3
k-Nearest Neighbour Classification
as.table.confusionMatrix
Save Confusion Table Results
predictors
List predictors used in the model
applyProcessing
Data Processing on Predictor Variables (Deprecated)