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caret (version 6.0-24)
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
208,749
Version
6.0-24
License
GPL-2
Maintainer
Max Kuhn
Last Published
February 16th, 2014
Functions in caret (6.0-24)
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BoxCoxTrans.default
Box-Cox and Exponential Transformations
createDataPartition
Data Splitting functions
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
downSample
Down- and Up-Sampling Imbalanced Data
dotPlot
Create a dotplot of variable importance values
plot.varImp.train
Plotting variable importance measures
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
dhfr
Dihydrofolate Reductase Inhibitors Data
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
cox2
COX-2 Activity Data
knn3
k-Nearest Neighbour Classification
BloodBrain
Blood Brain Barrier Data
histogram.train
Lattice functions for plotting resampling results
avNNet.default
Neural Networks Using Model Averaging
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
caret-internal
Internal Functions
nearZeroVar
Identification of near zero variance predictors
cars
Kelly Blue Book resale data for 2005 model year GM cars
bagEarth
Bagged Earth
modelLookup
Tools for Models Available in
train
confusionMatrix.train
Estimate a Resampled Confusion Matrix
format.bagEarth
Format 'bagEarth' objects
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
panel.needle
Needle Plot Lattice Panel
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
plot.train
Plot Method for the train Class
sensitivity
Calculate sensitivity, specificity and predictive values
rfeControl
Controlling the Feature Selection Algorithms
postResample
Calculates performance across resamples
dummyVars
Create A Full Set of Dummy Variables
panel.lift2
Lattice Panel Functions for Lift Plots
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
classDist
Compute and predict the distances to class centroids
predict.bagEarth
Predicted values based on bagged Earth and FDA models
summary.bagEarth
Summarize a bagged earth or FDA fit
bagFDA
Bagged FDA
varImp
Calculation of variable importance for regression and classification models
segmentationData
Cell Body Segmentation
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
rfe
Backwards Feature Selection
predict.knn3
Predictions from k-Nearest Neighbors
oneSE
Selecting tuning Parameters
bag.default
A General Framework For Bagging
predict.train
Extract predictions and class probabilities from train objects
findCorrelation
Determine highly correlated variables
tecator
Fat, Water and Protein Content of Meat Samples
icr.formula
Independent Component Regression
twoClassSim
Two-Class Simulations
lift
Lift Plot
GermanCredit
German Credit Data
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
filterVarImp
Calculation of filter-based variable importance
prcomp.resamples
Principal Components Analysis of Resampling Results
print.train
Print Method for the train Class
pcaNNet.default
Neural Networks with a Principal Component Step
trainControl
Control parameters for train
update.train
Update or Re-fit a Model
oil
Fatty acid composition of commercial oils
sbfControl
Control Object for Selection By Filtering (SBF)
print.confusionMatrix
Print method for confusionMatrix
resampleSummary
Summary of resampled performance estimates
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
sbf
Selection By Filtering (SBF)
confusionMatrix
Create a confusion matrix
maxDissim
Maximum Dissimilarity Sampling
plotClassProbs
Plot Predicted Probabilities in Classification Models
nullModel
Fit a simple, non-informative model
caretFuncs
Backwards Feature Selection Helper Functions
resampleHist
Plot the resampling distribution of the model statistics
spatialSign
Compute the multivariate spatial sign
knnreg
k-Nearest Neighbour Regression
caretSBF
Selection By Filtering (SBF) Helper Functions
preProcess
Pre-Processing of Predictors
as.table.confusionMatrix
Save Confusion Table Results
diff.resamples
Inferential Assessments About Model Performance
findLinearCombos
Determine linear combinations in a matrix
plot.rfe
Plot RFE Performance Profiles
predictors
List predictors used in the model
resamples
Collation and Visualization of Resampling Results
pottery
Pottery from Pre-Classical Sites in Italy
calibration
Probability Calibration Plot
train
Fit Predictive Models over Different Tuning Parameters