Rdocumentation
powered by
Learn R Programming
⚠️
There's a newer version (7.0-1) of this package.
Take me there.
caret (version 4.87)
Classification and Regression Training
Description
Misc functions for training and plotting classification and regression models
Copy Link
Link to current version
Version
Version
7.0-1
6.0-94
6.0-93
6.0-92
6.0-91
6.0-90
6.0-89
6.0-88
6.0-86
6.0-85
6.0-84
6.0-83
6.0-82
6.0-81
6.0-80
6.0-79
6.0-78
6.0-77
6.0-76
6.0-73
6.0-72
6.0-71
6.0-70
6.0-68
6.0-64
6.0-62
6.0-58
6.0-57
6.0-52
6.0-47
6.0-41
6.0-37
6.0-35
6.0-34
6.0-30
6.0-29
6.0-24
6.0-22
6.0-21
5.17-7
5.16-24
5.16-04
5.15-61
5.15-052
5.15-048
5.15-045
5.15-044
5.15-023
5.14-023
5.13-037
5.13-20
5.12-04
5.11-06
5.10-13
5.09-012
5.09-006
5.08-011
5.07-024
5.07-005
5.07-001
5.05.004
5.04-007
5.03-003
5.02-011
5.01-001
4.99
4.98
4.92
4.91
4.90
4.89
4.88
4.87
4.85
4.83
4.78
4.77
4.76
4.75
4.73
4.72
4.70
4.69
4.68
4.67
4.65
4.64
4.63
4.62
4.61
4.60
4.59
4.58
4.57
4.54
4.53
4.51
4.49
4.48
4.47
4.45
4.44
4.43
4.42
4.41
4.39
4.37
4.36
4.34
4.33
4.31
4.30
4.27
4.26
4.25
4.24
4.23
4.20
4.19
4.18
4.17
4.16
4.15
4.12
4.11
4.10
4.08
4.06
4.05
3.51
3.45
3.37
3.32
3.25
3.21
3.16
3.13
3.12
3.08
2.29
2.27
Install
install.packages('caret')
Monthly Downloads
158,845
Version
4.87
License
GPL-2
Maintainer
Max Kuhn
Last Published
April 28th, 2011
Functions in caret (4.87)
Search all functions
createDataPartition
Data Splitting functions
icr.formula
Independent Component Regression
applyProcessing
Data Processing on Predictor Variables (Deprecated)
confusionMatrix
Create a confusion matrix
bagEarth
Bagged Earth
prcomp.resamples
Principal Components Analysis of Resampling Results
filterVarImp
Calculation of filter-based variable importance
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
print.train
Print Method for the train Class
knn3
k-Nearest Neighbour Classification
findLinearCombos
Determine linear combinations in a matrix
train
Fit Predictive Models over Different Tuning Parameters
createGrid
Tuning Parameter Grid
predict.bagEarth
Predicted values based on bagged Earth and FDA models
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
cox2
COX-2 Activity Data
diff.resamples
Inferential Assessments About Model Performance
GermanCredit
German Credit Data
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
sensitivity
Calculate sensitivity, specificity and predictive values
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
predict.knn3
Predictions from k-Nearest Neighbors
plotClassProbs
Plot Predicted Probabilities in Classification Models
oil
Fatty acid composition of commercial oils
pottery
Pottery from Pre-Classical Sites in Italy
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
panel.needle
Needle Plot Lattice Panel
cars
Kelly Blue Book resale data for 2005 model year GM cars
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
bag.default
A General Framework For Bagging
resamples
Collation and Visualization of Resampling Results
tecator
Fat, Water and Protein Content of Meat Samples
preProcess
Pre-Processing of Predictors
aucRoc
Compute the area under an ROC curve
findCorrelation
Determine highly correlated variables
BloodBrain
Blood Brain Barrier Data
caretSBF
Selection By Filtering (SBF) Helper Functions
caret-internal
Internal Functions
resampleHist
Plot the resampling distribution of the model statistics
roc
Compute the points for an ROC curve
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
caretFuncs
Backwards Feature Selection Helper Functions
bagFDA
Bagged FDA
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
knnreg
k-Nearest Neighbour Regression
dummyVars
Create A Full Set of Dummy Variables
print.confusionMatrix
Print method for confusionMatrix
varImp
Calculation of variable importance for regression and classification models
nullModel
Fit a simple, non-informative model
BoxCoxTrans.default
Box-Cox Transformations
as.table.confusionMatrix
Save Confusion Table Results
classDist
Compute and predict the distances to class centroids
histogram.train
Lattice functions for plotting resampling results
sbf
Selection By Filtering (SBF)
sbfControl
Control Object for Selection By Filtering (SBF)
dhfr
Dihydrofolate Reductase Inhibitors Data
predictors
List predictors used in the model
maxDissim
Maximum Dissimilarity Sampling
resampleSummary
Summary of resampled performance estimates
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
nearZeroVar
Identification of near zero variance predictors
rfeControl
Controlling the Feature Selection Algorithms
dotPlot
Create a dotplot of variable importance values
modelLookup
Descriptions Of Models Available in train()
rfe
Backwards Feature Selection
trainControl
Control parameters for train
spatialSign
Compute the multivariate spatial sign
format.bagEarth
Format 'bagEarth' objects
predict.train
Extract predictions and class probabilities from train objects
postResample
Calculates performance across resamples
summary.bagEarth
Summarize a bagged earth or FDA fit
plot.train
Plot Method for the train Class
pcaNNet.default
Neural Networks with a Principal Component Step
segmentationData
Cell Body Segmentation
oneSE
Selecting tuning Parameters
plot.varImp.train
Plotting variable importance measures