Rdocumentation
powered by
Learn R Programming
⚠️
There's a newer version (7.0-1) of this package.
Take me there.
caret (version 5.07-001)
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
214,321
Version
5.07-001
License
GPL-2
Maintainer
Max Kuhn
Last Published
October 23rd, 2011
Functions in caret (5.07-001)
Search all functions
BloodBrain
Blood Brain Barrier Data
GermanCredit
German Credit Data
as.table.confusionMatrix
Save Confusion Table Results
aucRoc
Compute the area under an ROC curve
avNNet.default
Neural Networks Using Model Averaging
bagEarth
Bagged Earth
bagFDA
Bagged FDA
caret-internal
Internal Functions
classDist
Compute and predict the distances to class centroids
confusionMatrix
Create a confusion matrix
confusionMatrix.train
Estimate a Resampled Confusion Matrix
cars
Kelly Blue Book resale data for 2005 model year GM cars
cox2
COX-2 Activity Data
createDataPartition
Data Splitting functions
createGrid
Tuning Parameter Grid
bag.default
A General Framework For Bagging
diff.resamples
Inferential Assessments About Model Performance
dhfr
Dihydrofolate Reductase Inhibitors Data
dotPlot
Create a dotplot of variable importance values
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
predict.train
Extract predictions and class probabilities from train objects
filterVarImp
Calculation of filter-based variable importance
dummyVars
Create A Full Set of Dummy Variables
findLinearCombos
Determine linear combinations in a matrix
format.bagEarth
Format 'bagEarth' objects
BoxCoxTrans.default
Box-Cox Transformations
knnreg
k-Nearest Neighbour Regression
histogram.train
Lattice functions for plotting resampling results
knn3
k-Nearest Neighbour Classification
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
lift
Lift Plot
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
nearZeroVar
Identification of near zero variance predictors
icr.formula
Independent Component Regression
maxDissim
Maximum Dissimilarity Sampling
modelLookup
Descriptions Of Models Available in train()
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
panel.lift2
Lattice Panel Functions for Lift Plots
nullModel
Fit a simple, non-informative model
plotClassProbs
Plot Predicted Probabilities in Classification Models
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
postResample
Calculates performance across resamples
plot.varImp.train
Plotting variable importance measures
pottery
Pottery from Pre-Classical Sites in Italy
oil
Fatty acid composition of commercial oils
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
prcomp.resamples
Principal Components Analysis of Resampling Results
print.confusionMatrix
Print method for confusionMatrix
predictors
List predictors used in the model
panel.needle
Needle Plot Lattice Panel
plot.train
Plot Method for the train Class
resampleHist
Plot the resampling distribution of the model statistics
print.train
Print Method for the train Class
pcaNNet.default
Neural Networks with a Principal Component Step
resamples
Collation and Visualization of Resampling Results
resampleSummary
Summary of resampled performance estimates
rfeControl
Controlling the Feature Selection Algorithms
roc
Compute the points for an ROC curve
caretSBF
Selection By Filtering (SBF) Helper Functions
sbf
Selection By Filtering (SBF)
oneSE
Selecting tuning Parameters
summary.bagEarth
Summarize a bagged earth or FDA fit
segmentationData
Cell Body Segmentation
spatialSign
Compute the multivariate spatial sign
caretFuncs
Backwards Feature Selection Helper Functions
sensitivity
Calculate sensitivity, specificity and predictive values
findCorrelation
Determine highly correlated variables
sbfControl
Control Object for Selection By Filtering (SBF)
tecator
Fat, Water and Protein Content of Meat Samples
train
Fit Predictive Models over Different Tuning Parameters
varImp
Calculation of variable importance for regression and classification models
trainControl
Control parameters for train
predict.knn3
Predictions from k-Nearest Neighbors
predict.bagEarth
Predicted values based on bagged Earth and FDA models
rfe
Backwards Feature Selection
preProcess
Pre-Processing of Predictors