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caret (version 5.16-04)
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
5.16-04
License
GPL-2
Maintainer
Max Kuhn
Last Published
May 17th, 2013
Functions in caret (5.16-04)
Search functions
calibration
Probability Calibration Plot
icr.formula
Independent Component Regression
bag.default
A General Framework For Bagging
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
plotClassProbs
Plot Predicted Probabilities in Classification Models
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
findLinearCombos
Determine linear combinations in a matrix
createGrid
Tuning Parameter Grid
createDataPartition
Data Splitting functions
BloodBrain
Blood Brain Barrier Data
predictors
List predictors used in the model
GermanCredit
German Credit Data
dotPlot
Create a dotplot of variable importance values
knn3
k-Nearest Neighbour Classification
sbfControl
Control Object for Selection By Filtering (SBF)
sensitivity
Calculate sensitivity, specificity and predictive values
knnreg
k-Nearest Neighbour Regression
update.train
Update and Re-fit a Model
classDist
Compute and predict the distances to class centroids
confusionMatrix.train
Estimate a Resampled Confusion Matrix
caretFuncs
Backwards Feature Selection Helper Functions
filterVarImp
Calculation of filter-based variable importance
dhfr
Dihydrofolate Reductase Inhibitors Data
downSample
Down- and Up-Sampling Imbalanced Data
maxDissim
Maximum Dissimilarity Sampling
dummyVars
Create A Full Set of Dummy Variables
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
panel.lift2
Lattice Panel Functions for Lift Plots
caret-internal
Internal Functions
rfeControl
Controlling the Feature Selection Algorithms
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
sbf
Selection By Filtering (SBF)
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
segmentationData
Cell Body Segmentation
confusionMatrix
Create a confusion matrix
bagFDA
Bagged FDA
nullModel
Fit a simple, non-informative model
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
diff.resamples
Inferential Assessments About Model Performance
prcomp.resamples
Principal Components Analysis of Resampling Results
cox2
COX-2 Activity Data
histogram.train
Lattice functions for plotting resampling results
resamples
Collation and Visualization of Resampling Results
modelLookup
Descriptions Of Models Available in train()
rfe
Backwards Feature Selection
plot.train
Plot Method for the train Class
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
oil
Fatty acid composition of commercial oils
preProcess
Pre-Processing of Predictors
predict.train
Extract predictions and class probabilities from train objects
as.table.confusionMatrix
Save Confusion Table Results
nearZeroVar
Identification of near zero variance predictors
summary.bagEarth
Summarize a bagged earth or FDA fit
predict.knn3
Predictions from k-Nearest Neighbors
tecator
Fat, Water and Protein Content of Meat Samples
resampleHist
Plot the resampling distribution of the model statistics
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
pcaNNet.default
Neural Networks with a Principal Component Step
print.train
Print Method for the train Class
twoClassSim
Two-Class Simulations
plot.varImp.train
Plotting variable importance measures
trainControl
Control parameters for train
oneSE
Selecting tuning Parameters
varImp
Calculation of variable importance for regression and classification models
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
BoxCoxTrans.default
Box-Cox Transformations
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
caretSBF
Selection By Filtering (SBF) Helper Functions
spatialSign
Compute the multivariate spatial sign
findCorrelation
Determine highly correlated variables
bagEarth
Bagged Earth
cars
Kelly Blue Book resale data for 2005 model year GM cars
resampleSummary
Summary of resampled performance estimates
pottery
Pottery from Pre-Classical Sites in Italy
panel.needle
Needle Plot Lattice Panel
predict.bagEarth
Predicted values based on bagged Earth and FDA models
avNNet.default
Neural Networks Using Model Averaging
format.bagEarth
Format 'bagEarth' objects
lift
Lift Plot
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
postResample
Calculates performance across resamples
print.confusionMatrix
Print method for confusionMatrix