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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
Max Kuhn
Last Published
August 5th, 2013
Functions in caret (5.17-7)
Search all functions
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