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caret (version 5.15-045)
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
185,160
Version
5.15-045
License
GPL-2
Maintainer
Max Kuhn
Last Published
November 27th, 2012
Functions in caret (5.15-045)
Search functions
bagFDA
Bagged FDA
diff.resamples
Inferential Assessments About Model Performance
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
dhfr
Dihydrofolate Reductase Inhibitors Data
caret-internal
Internal Functions
createDataPartition
Data Splitting functions
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
segmentationData
Cell Body Segmentation
icr.formula
Independent Component Regression
knnreg
k-Nearest Neighbour Regression
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
findLinearCombos
Determine linear combinations in a matrix
pcaNNet.default
Neural Networks with a Principal Component Step
plotClassProbs
Plot Predicted Probabilities in Classification Models
as.table.confusionMatrix
Save Confusion Table Results
GermanCredit
German Credit Data
caretSBF
Selection By Filtering (SBF) Helper Functions
knn3
k-Nearest Neighbour Classification
spatialSign
Compute the multivariate spatial sign
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
pottery
Pottery from Pre-Classical Sites in Italy
panel.lift2
Lattice Panel Functions for Lift Plots
rfe
Backwards Feature Selection
sensitivity
Calculate sensitivity, specificity and predictive values
print.confusionMatrix
Print method for confusionMatrix
prcomp.resamples
Principal Components Analysis of Resampling Results
format.bagEarth
Format 'bagEarth' objects
modelLookup
Descriptions Of Models Available in train()
findCorrelation
Determine highly correlated variables
BloodBrain
Blood Brain Barrier Data
caretFuncs
Backwards Feature Selection Helper Functions
histogram.train
Lattice functions for plotting resampling results
plot.train
Plot Method for the train Class
maxDissim
Maximum Dissimilarity Sampling
bag.default
A General Framework For Bagging
lift
Lift Plot
calibration
Probability Calibration Plot
sbfControl
Control Object for Selection By Filtering (SBF)
panel.needle
Needle Plot Lattice Panel
oneSE
Selecting tuning Parameters
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
trainControl
Control parameters for train
confusionMatrix.train
Estimate a Resampled Confusion Matrix
dummyVars
Create A Full Set of Dummy Variables
plot.varImp.train
Plotting variable importance measures
predictors
List predictors used in the model
varImp
Calculation of variable importance for regression and classification models
confusionMatrix
Create a confusion matrix
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
resampleSummary
Summary of resampled performance estimates
nearZeroVar
Identification of near zero variance predictors
summary.bagEarth
Summarize a bagged earth or FDA fit
oil
Fatty acid composition of commercial oils
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
predict.knn3
Predictions from k-Nearest Neighbors
resampleHist
Plot the resampling distribution of the model statistics
avNNet.default
Neural Networks Using Model Averaging
rfeControl
Controlling the Feature Selection Algorithms
dotPlot
Create a dotplot of variable importance values
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
bagEarth
Bagged Earth
createGrid
Tuning Parameter Grid
nullModel
Fit a simple, non-informative model
postResample
Calculates performance across resamples
sbf
Selection By Filtering (SBF)
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
filterVarImp
Calculation of filter-based variable importance
update.train
Update and Re-fit a Model
print.train
Print Method for the train Class
predict.bagEarth
Predicted values based on bagged Earth and FDA models
resamples
Collation and Visualization of Resampling Results
classDist
Compute and predict the distances to class centroids
tecator
Fat, Water and Protein Content of Meat Samples
BoxCoxTrans.default
Box-Cox Transformations
cox2
COX-2 Activity Data
downSample
Down- and Up-Sampling Imbalanced Data
predict.train
Extract predictions and class probabilities from train objects
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
cars
Kelly Blue Book resale data for 2005 model year GM cars
preProcess
Pre-Processing of Predictors