Rdocumentation
powered by
Learn R Programming
⚠️
There's a newer version (7.0-1) of this package.
Take me there.
caret (version 5.09-006)
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
138,220
Version
5.09-006
License
GPL-2
Maintainer
Max Kuhn
Last Published
December 7th, 2011
Functions in caret (5.09-006)
Search all functions
caret-internal
Internal Functions
confusionMatrix.train
Estimate a Resampled Confusion Matrix
bag.default
A General Framework For Bagging
aucRoc
Compute the area under an ROC curve
classDist
Compute and predict the distances to class centroids
icr.formula
Independent Component Regression
caretSBF
Selection By Filtering (SBF) Helper Functions
confusionMatrix
Create a confusion matrix
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
bagFDA
Bagged FDA
dhfr
Dihydrofolate Reductase Inhibitors Data
avNNet.default
Neural Networks Using Model Averaging
filterVarImp
Calculation of filter-based variable importance
maxDissim
Maximum Dissimilarity Sampling
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
nullModel
Fit a simple, non-informative model
sensitivity
Calculate sensitivity, specificity and predictive values
diff.resamples
Inferential Assessments About Model Performance
pcaNNet.default
Neural Networks with a Principal Component Step
sbf
Selection By Filtering (SBF)
findCorrelation
Determine highly correlated variables
knnreg
k-Nearest Neighbour Regression
summary.bagEarth
Summarize a bagged earth or FDA fit
BloodBrain
Blood Brain Barrier Data
as.table.confusionMatrix
Save Confusion Table Results
sbfControl
Control Object for Selection By Filtering (SBF)
predict.bagEarth
Predicted values based on bagged Earth and FDA models
plotClassProbs
Plot Predicted Probabilities in Classification Models
preProcess
Pre-Processing of Predictors
tecator
Fat, Water and Protein Content of Meat Samples
createDataPartition
Data Splitting functions
oneSE
Selecting tuning Parameters
resamples
Collation and Visualization of Resampling Results
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
cox2
COX-2 Activity Data
rfeControl
Controlling the Feature Selection Algorithms
plot.train
Plot Method for the train Class
lift
Lift Plot
bagEarth
Bagged Earth
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
cars
Kelly Blue Book resale data for 2005 model year GM cars
prcomp.resamples
Principal Components Analysis of Resampling Results
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
knn3
k-Nearest Neighbour Classification
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
panel.lift2
Lattice Panel Functions for Lift Plots
format.bagEarth
Format 'bagEarth' objects
panel.needle
Needle Plot Lattice Panel
pottery
Pottery from Pre-Classical Sites in Italy
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
findLinearCombos
Determine linear combinations in a matrix
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
histogram.train
Lattice functions for plotting resampling results
modelLookup
Descriptions Of Models Available in train()
nearZeroVar
Identification of near zero variance predictors
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
varImp
Calculation of variable importance for regression and classification models
segmentationData
Cell Body Segmentation
caretFuncs
Backwards Feature Selection Helper Functions
rfe
Backwards Feature Selection
roc
Compute the points for an ROC curve
print.confusionMatrix
Print method for confusionMatrix
predict.knn3
Predictions from k-Nearest Neighbors
resampleHist
Plot the resampling distribution of the model statistics
train
Fit Predictive Models over Different Tuning Parameters
BoxCoxTrans.default
Box-Cox Transformations
dotPlot
Create a dotplot of variable importance values
dummyVars
Create A Full Set of Dummy Variables
createGrid
Tuning Parameter Grid
oil
Fatty acid composition of commercial oils
resampleSummary
Summary of resampled performance estimates
GermanCredit
German Credit Data
plot.varImp.train
Plotting variable importance measures
predict.train
Extract predictions and class probabilities from train objects
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
spatialSign
Compute the multivariate spatial sign
postResample
Calculates performance across resamples
trainControl
Control parameters for train
predictors
List predictors used in the model
print.train
Print Method for the train Class