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caret (version 6.0-22)
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
6.0-22
License
GPL-2
Maintainer
Max Kuhn
Last Published
January 18th, 2014
Functions in caret (6.0-22)
Search functions
cox2
COX-2 Activity Data
GermanCredit
German Credit Data
bag.default
A General Framework For Bagging
bagFDA
Bagged FDA
format.bagEarth
Format 'bagEarth' objects
caret-internal
Internal Functions
BoxCoxTrans.default
Box-Cox and Exponential Transformations
postResample
Calculates performance across resamples
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
createDataPartition
Data Splitting functions
oil
Fatty acid composition of commercial oils
dotPlot
Create a dotplot of variable importance values
histogram.train
Lattice functions for plotting resampling results
dummyVars
Create A Full Set of Dummy Variables
cars
Kelly Blue Book resale data for 2005 model year GM cars
avNNet.default
Neural Networks Using Model Averaging
plotClassProbs
Plot Predicted Probabilities in Classification Models
maxDissim
Maximum Dissimilarity Sampling
preProcess
Pre-Processing of Predictors
print.train
Print Method for the train Class
prcomp.resamples
Principal Components Analysis of Resampling Results
predictors
List predictors used in the model
pcaNNet.default
Neural Networks with a Principal Component Step
rfeControl
Controlling the Feature Selection Algorithms
classDist
Compute and predict the distances to class centroids
nullModel
Fit a simple, non-informative model
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
BloodBrain
Blood Brain Barrier Data
downSample
Down- and Up-Sampling Imbalanced Data
knnreg
k-Nearest Neighbour Regression
update.train
Update or Re-fit a Model
panel.lift2
Lattice Panel Functions for Lift Plots
plot.rfe
Plot RFE Performance Profiles
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
pottery
Pottery from Pre-Classical Sites in Italy
diff.resamples
Inferential Assessments About Model Performance
rfe
Backwards Feature Selection
bagEarth
Bagged Earth
caretSBF
Selection By Filtering (SBF) Helper Functions
predict.knn3
Predictions from k-Nearest Neighbors
findLinearCombos
Determine linear combinations in a matrix
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
resampleSummary
Summary of resampled performance estimates
nearZeroVar
Identification of near zero variance predictors
tecator
Fat, Water and Protein Content of Meat Samples
print.confusionMatrix
Print method for confusionMatrix
findCorrelation
Determine highly correlated variables
predict.train
Extract predictions and class probabilities from train objects
icr.formula
Independent Component Regression
oneSE
Selecting tuning Parameters
filterVarImp
Calculation of filter-based variable importance
plot.train
Plot Method for the train Class
predict.bagEarth
Predicted values based on bagged Earth and FDA models
modelLookup
Tools for Models Available in
train
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
confusionMatrix.train
Estimate a Resampled Confusion Matrix
as.table.confusionMatrix
Save Confusion Table Results
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
varImp
Calculation of variable importance for regression and classification models
panel.needle
Needle Plot Lattice Panel
sbf
Selection By Filtering (SBF)
sbfControl
Control Object for Selection By Filtering (SBF)
summary.bagEarth
Summarize a bagged earth or FDA fit
calibration
Probability Calibration Plot
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
lift
Lift Plot
knn3
k-Nearest Neighbour Classification
plot.varImp.train
Plotting variable importance measures
resamples
Collation and Visualization of Resampling Results
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
segmentationData
Cell Body Segmentation
confusionMatrix
Create a confusion matrix
sensitivity
Calculate sensitivity, specificity and predictive values
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
dhfr
Dihydrofolate Reductase Inhibitors Data
caretFuncs
Backwards Feature Selection Helper Functions
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
resampleHist
Plot the resampling distribution of the model statistics
trainControl
Control parameters for train
spatialSign
Compute the multivariate spatial sign
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
twoClassSim
Two-Class Simulations
train
Fit Predictive Models over Different Tuning Parameters