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caret (version 3.51)
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
230,598
Version
3.51
License
GPL-2
Maintainer
Max Kuhn
Last Published
December 10th, 2024
Functions in caret (3.51)
Search all functions
predict.knn3
Predictions from k-Nearest Neighbors
predict.train
Extract predictions and class probabilities from train objects
bagEarth
Bagged Earth
knn3
k-Nearest Neighbour Classification
dotPlot
Create a dotplot of variable importance values
print.confusionMatrix
Print method for confusionMatrix
plsda
Partial Least Squares Discriminant Analysis
nearZeroVar
Identification of near zero variance predictors
print.train
Print Method for the train Class
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
roc
Compute the points for an ROC curve
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
createGrid
Tuning Parameter Grid
format.bagEarth
Format 'bagEarth' objects
plot.varImp.train
Plotting variable importance measures
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
applyProcessing
Data Processing on Predictor Variables (Deprecated)
BloodBrain
Blood Brain Barrier Data
preProcess
Pre-Processing of Predictors
resampleSummary
Summary of resampled performance estimates
panel.needle
Needle Plot Lattice Panel
oil
Fatty acid composition of commercial oils
trainControl
Control parameters for train
train
Fit Predictive Models over Different Tuning Parameters
spatialSign
Compute the multivariate spatial sign
confusionMatrix
Create a confusion matrix
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
plot.train
Plot Method for the train Class
sensitivity
Calculate Sensitivity, Specificity and predictive values
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
predict.bagEarth
Predicted values based on bagged Earth and FDA models
pcaNNet.default
Neural Networks with a Principal Component Step
filterVarImp
Calculation of filter-based variable importance
pottery
Pottery from Pre-Classical Sites in Italy
resampleHist
Plot the resampling distribution of the model statistics
varImp
Calculation of variable importance for regression and classification models
summary.bagEarth
Summarize a bagged earth or FDA fit
maxDissim
Maximum Dissimilarity Sampling
bagFDA
Bagged FDA
oneSE
Selecting tuning Parameters
postResample
Calculates performance across resamples
createDataPartition
Data Splitting functions
aucRoc
Compute the area under an ROC curve
caret-internal
Internal Functions
predictors
List predictors used in the model
histogram.train
Lattice functions for plotting resampling results
plotClassProbs
Plot Predicted Probabilities in Classification Models
findCorrelation
Determine highly correlated variables
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
findLinearCombos
Determine linear combinations in a matrix
tecator
Fat, Water and Protein Content of Maat Samples
cox2
COX-2 Activity Data