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caret (version 5.17-7)

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

221,361

Version

5.17-7

License

GPL-2

Maintainer

Last Published

August 5th, 2013

Functions in caret (5.17-7)

dotplot.diff.resamples

Lattice Functions for Visualizing Resampling Differences
dhfr

Dihydrofolate Reductase Inhibitors Data
Alternate Affy Gene Expression Summary Methods.

Generate Expression Values from Probes
findCorrelation

Determine highly correlated variables
lattice.rfe

Lattice functions for plotting resampling results of recursive feature selection
confusionMatrix

Create a confusion matrix
bag.default

A General Framework For Bagging
bagEarth

Bagged Earth
findLinearCombos

Determine linear combinations in a matrix
as.table.confusionMatrix

Save Confusion Table Results
GermanCredit

German Credit Data
lift

Lift Plot
print.confusionMatrix

Print method for confusionMatrix
classDist

Compute and predict the distances to class centroids
BloodBrain

Blood Brain Barrier Data
bagFDA

Bagged FDA
calibration

Probability Calibration Plot
BoxCoxTrans.default

Box-Cox and Exponential Transformations
pcaNNet.default

Neural Networks with a Principal Component Step
caret-internal

Internal Functions
filterVarImp

Calculation of filter-based variable importance
resampleSummary

Summary of resampled performance estimates
caretSBF

Selection By Filtering (SBF) Helper Functions
nearZeroVar

Identification of near zero variance predictors
dummyVars

Create A Full Set of Dummy Variables
oil

Fatty acid composition of commercial oils
plsda

Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
mdrr

Multidrug Resistance Reversal (MDRR) Agent Data
plot.train

Plot Method for the train Class
predict.train

Extract predictions and class probabilities from train objects
twoClassSim

Two-Class Simulations
panel.lift2

Lattice Panel Functions for Lift Plots
downSample

Down- and Up-Sampling Imbalanced Data
createDataPartition

Data Splitting functions
cars

Kelly Blue Book resale data for 2005 model year GM cars
avNNet.default

Neural Networks Using Model Averaging
predict.knnreg

Predictions from k-Nearest Neighbors Regression Model
resampleHist

Plot the resampling distribution of the model statistics
resamples

Collation and Visualization of Resampling Results
maxDissim

Maximum Dissimilarity Sampling
summary.bagEarth

Summarize a bagged earth or FDA fit
segmentationData

Cell Body Segmentation
knnreg

k-Nearest Neighbour Regression
spatialSign

Compute the multivariate spatial sign
sensitivity

Calculate sensitivity, specificity and predictive values
featurePlot

Wrapper for Lattice Plotting of Predictor Variables
predict.knn3

Predictions from k-Nearest Neighbors
histogram.train

Lattice functions for plotting resampling results
diff.resamples

Inferential Assessments About Model Performance
normalize.AffyBatch.normalize2Reference

Quantile Normalization to a Reference Distribution
format.bagEarth

Format 'bagEarth' objects
pottery

Pottery from Pre-Classical Sites in Italy
preProcess

Pre-Processing of Predictors
plotClassProbs

Plot Predicted Probabilities in Classification Models
confusionMatrix.train

Estimate a Resampled Confusion Matrix
plot.varImp.train

Plotting variable importance measures
print.train

Print Method for the train Class
xyplot.resamples

Lattice Functions for Visualizing Resampling Results
panel.needle

Needle Plot Lattice Panel
trainControl

Control parameters for train
predict.bagEarth

Predicted values based on bagged Earth and FDA models
sbf

Selection By Filtering (SBF)
oneSE

Selecting tuning Parameters
tecator

Fat, Water and Protein Content of Meat Samples
postResample

Calculates performance across resamples
plotObsVsPred

Plot Observed versus Predicted Results in Regression and Classification Models
varImp

Calculation of variable importance for regression and classification models
sbfControl

Control Object for Selection By Filtering (SBF)
dotPlot

Create a dotplot of variable importance values
knn3

k-Nearest Neighbour Classification
normalize2Reference

Quantile Normalize Columns of a Matrix Based on a Reference Distribution
update.train

Update and Re-fit a Model
createGrid

Tuning Parameter Grid
cox2

COX-2 Activity Data
icr.formula

Independent Component Regression
modelLookup

Descriptions Of Models Available in train()
nullModel

Fit a simple, non-informative model
prcomp.resamples

Principal Components Analysis of Resampling Results
caretFuncs

Backwards Feature Selection Helper Functions
predictors

List predictors used in the model
rfeControl

Controlling the Feature Selection Algorithms
rfe

Backwards Feature Selection
train

Fit Predictive Models over Different Tuning Parameters