RDocumentation
Moon
Learn R
Search all packages and functions
⚠️
There's a newer version (6.0-94) of this package.
Take me there.
caret (version 5.07-024)
Classification and Regression Training
Description
Misc functions for training and plotting classification and regression models
Copy Link
Copy
Link to current version
Version
Version
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
Down Chevron
Install
install.packages('caret')
Monthly Downloads
160,352
Version
5.07-024
License
GPL-2
Maintainer
Max Kuhn
Last Published
November 14th, 2011
Functions in caret (5.07-024)
Search functions
findCorrelation
Determine highly correlated variables
aucRoc
Compute the area under an ROC curve
GermanCredit
German Credit Data
diff.resamples
Inferential Assessments About Model Performance
caret-internal
Internal Functions
createDataPartition
Data Splitting functions
caretFuncs
Backwards Feature Selection Helper Functions
plotClassProbs
Plot Predicted Probabilities in Classification Models
plot.varImp.train
Plotting variable importance measures
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
print.confusionMatrix
Print method for confusionMatrix
pcaNNet.default
Neural Networks with a Principal Component Step
tecator
Fat, Water and Protein Content of Meat Samples
oil
Fatty acid composition of commercial oils
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
summary.bagEarth
Summarize a bagged earth or FDA fit
oneSE
Selecting tuning Parameters
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
plot.train
Plot Method for the train Class
resamples
Collation and Visualization of Resampling Results
findLinearCombos
Determine linear combinations in a matrix
resampleSummary
Summary of resampled performance estimates
varImp
Calculation of variable importance for regression and classification models
postResample
Calculates performance across resamples
resampleHist
Plot the resampling distribution of the model statistics
sensitivity
Calculate sensitivity, specificity and predictive values
predict.knn3
Predictions from k-Nearest Neighbors
knnreg
k-Nearest Neighbour Regression
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
segmentationData
Cell Body Segmentation
bag.default
A General Framework For Bagging
nearZeroVar
Identification of near zero variance predictors
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
spatialSign
Compute the multivariate spatial sign
sbf
Selection By Filtering (SBF)
knn3
k-Nearest Neighbour Classification
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
histogram.train
Lattice functions for plotting resampling results
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
bagEarth
Bagged Earth
cars
Kelly Blue Book resale data for 2005 model year GM cars
roc
Compute the points for an ROC curve
panel.needle
Needle Plot Lattice Panel
caretSBF
Selection By Filtering (SBF) Helper Functions
format.bagEarth
Format 'bagEarth' objects
panel.lift2
Lattice Panel Functions for Lift Plots
filterVarImp
Calculation of filter-based variable importance
bagFDA
Bagged FDA
rfe
Backwards Feature Selection
predictors
List predictors used in the model
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
lift
Lift Plot
BloodBrain
Blood Brain Barrier Data
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
prcomp.resamples
Principal Components Analysis of Resampling Results
avNNet.default
Neural Networks Using Model Averaging
dotPlot
Create a dotplot of variable importance values
predict.train
Extract predictions and class probabilities from train objects
sbfControl
Control Object for Selection By Filtering (SBF)
confusionMatrix.train
Estimate a Resampled Confusion Matrix
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
as.table.confusionMatrix
Save Confusion Table Results
rfeControl
Controlling the Feature Selection Algorithms
preProcess
Pre-Processing of Predictors
trainControl
Control parameters for train
createGrid
Tuning Parameter Grid
BoxCoxTrans.default
Box-Cox Transformations
icr.formula
Independent Component Regression
classDist
Compute and predict the distances to class centroids
cox2
COX-2 Activity Data
nullModel
Fit a simple, non-informative model
dhfr
Dihydrofolate Reductase Inhibitors Data
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
modelLookup
Descriptions Of Models Available in train()
confusionMatrix
Create a confusion matrix
print.train
Print Method for the train Class
pottery
Pottery from Pre-Classical Sites in Italy
predict.bagEarth
Predicted values based on bagged Earth and FDA models
train
Fit Predictive Models over Different Tuning Parameters
dummyVars
Create A Full Set of Dummy Variables
maxDissim
Maximum Dissimilarity Sampling