Rdocumentation
powered by
Learn R Programming
⚠️
There's a newer version (7.0-1) of this package.
Take me there.
caret (version 5.15-052)
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
5.15-052
License
GPL-2
Maintainer
Max Kuhn
Last Published
January 17th, 2013
Functions in caret (5.15-052)
Search all functions
bagFDA
Bagged FDA
lift
Lift Plot
classDist
Compute and predict the distances to class centroids
bag.default
A General Framework For Bagging
dhfr
Dihydrofolate Reductase Inhibitors Data
GermanCredit
German Credit Data
findLinearCombos
Determine linear combinations in a matrix
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
segmentationData
Cell Body Segmentation
createDataPartition
Data Splitting functions
modelLookup
Descriptions Of Models Available in train()
downSample
Down- and Up-Sampling Imbalanced Data
panel.lift2
Lattice Panel Functions for Lift Plots
BoxCoxTrans.default
Box-Cox Transformations
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
format.bagEarth
Format 'bagEarth' objects
predict.knn3
Predictions from k-Nearest Neighbors
predict.bagEarth
Predicted values based on bagged Earth and FDA models
preProcess
Pre-Processing of Predictors
maxDissim
Maximum Dissimilarity Sampling
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
postResample
Calculates performance across resamples
sbfControl
Control Object for Selection By Filtering (SBF)
caretFuncs
Backwards Feature Selection Helper Functions
diff.resamples
Inferential Assessments About Model Performance
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
nullModel
Fit a simple, non-informative model
oil
Fatty acid composition of commercial oils
histogram.train
Lattice functions for plotting resampling results
pottery
Pottery from Pre-Classical Sites in Italy
spatialSign
Compute the multivariate spatial sign
confusionMatrix
Create a confusion matrix
cox2
COX-2 Activity Data
filterVarImp
Calculation of filter-based variable importance
plot.train
Plot Method for the train Class
dummyVars
Create A Full Set of Dummy Variables
rfe
Backwards Feature Selection
rfeControl
Controlling the Feature Selection Algorithms
cars
Kelly Blue Book resale data for 2005 model year GM cars
sbf
Selection By Filtering (SBF)
calibration
Probability Calibration Plot
update.train
Update and Re-fit a Model
confusionMatrix.train
Estimate a Resampled Confusion Matrix
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
dotPlot
Create a dotplot of variable importance values
resampleHist
Plot the resampling distribution of the model statistics
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
as.table.confusionMatrix
Save Confusion Table Results
trainControl
Control parameters for train
pcaNNet.default
Neural Networks with a Principal Component Step
findCorrelation
Determine highly correlated variables
summary.bagEarth
Summarize a bagged earth or FDA fit
panel.needle
Needle Plot Lattice Panel
print.confusionMatrix
Print method for confusionMatrix
caretSBF
Selection By Filtering (SBF) Helper Functions
oneSE
Selecting tuning Parameters
predict.train
Extract predictions and class probabilities from train objects
knnreg
k-Nearest Neighbour Regression
predictors
List predictors used in the model
avNNet.default
Neural Networks Using Model Averaging
sensitivity
Calculate sensitivity, specificity and predictive values
knn3
k-Nearest Neighbour Classification
plot.varImp.train
Plotting variable importance measures
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
tecator
Fat, Water and Protein Content of Meat Samples
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
prcomp.resamples
Principal Components Analysis of Resampling Results
varImp
Calculation of variable importance for regression and classification models
BloodBrain
Blood Brain Barrier Data
bagEarth
Bagged Earth
caret-internal
Internal Functions
createGrid
Tuning Parameter Grid
icr.formula
Independent Component Regression
plotClassProbs
Plot Predicted Probabilities in Classification Models
nearZeroVar
Identification of near zero variance predictors
print.train
Print Method for the train Class
resamples
Collation and Visualization of Resampling Results
resampleSummary
Summary of resampled performance estimates