Rdocumentation
powered by
Learn R Programming
⚠️
There's a newer version (7.0-1) of this package.
Take me there.
caret (version 4.39)
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
4.39
License
GPL-2
Maintainer
Max Kuhn
Last Published
May 16th, 2010
Functions in caret (4.39)
Search all functions
caret-internal
Internal Functions
dotPlot
Create a dotplot of variable importance values
predict.train
Extract predictions and class probabilities from train objects
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
nullModel
Fit a simple, non-informative model
panel.needle
Needle Plot Lattice Panel
print.train
Print Method for the train Class
createGrid
Tuning Parameter Grid
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
varImp
Calculation of variable importance for regression and classification models
as.table.confusionMatrix
Save Confusion Table Results
diff.resamples
Inferential Assessments About Model Performance
cars
Kelly Blue Book resale data for 2005 model year GM cars
findLinearCombos
Determine linear combinations in a matrix
plotClassProbs
Plot Predicted Probabilities in Classification Models
filterVarImp
Calculation of filter-based variable importance
classDist
Compute and predict the distances to class centroids
createDataPartition
Data Splitting functions
findCorrelation
Determine highly correlated variables
format.bagEarth
Format 'bagEarth' objects
oil
Fatty acid composition of commercial oils
print.confusionMatrix
Print method for confusionMatrix
rfe
Backwards Feature Selection
oneSE
Selecting tuning Parameters
sbfControl
Control Object for Selection By Filtering (SBF)
plot.varImp.train
Plotting variable importance measures
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
BloodBrain
Blood Brain Barrier Data
resamples
Collation and Visualization of Resampling Results
sensitivity
Calculate sensitivity, specificity and predictive values
train
Fit Predictive Models over Different Tuning Parameters
nearZeroVar
Identification of near zero variance predictors
resampleHist
Plot the resampling distribution of the model statistics
plot.train
Plot Method for the train Class
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
predict.knn3
Predictions from k-Nearest Neighbors
sbf
Selection By Filtering (SBF)
cox2
COX-2 Activity Data
pcaNNet.default
Neural Networks with a Principal Component Step
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
caretFuncs
Backwards Feature Selection Helper Functions
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
dhfr
Dihydrofolate Reductase Inhibitors Data
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
trainControl
Control parameters for train
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
bagFDA
Bagged FDA
knn3
k-Nearest Neighbour Classification
knnreg
k-Nearest Neighbour Regression
preProcess
Pre-Processing of Predictors
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
rfeControl
Controlling the Feature Selection Algorithms
tecator
Fat, Water and Protein Content of Meat Samples
bagEarth
Bagged Earth
caretSBF
Selection By Filtering (SBF) Helper Functions
postResample
Calculates performance across resamples
applyProcessing
Data Processing on Predictor Variables (Deprecated)
maxDissim
Maximum Dissimilarity Sampling
summary.bagEarth
Summarize a bagged earth or FDA fit
spatialSign
Compute the multivariate spatial sign
pottery
Pottery from Pre-Classical Sites in Italy
roc
Compute the points for an ROC curve
predictors
List predictors used in the model
confusionMatrix
Create a confusion matrix
aucRoc
Compute the area under an ROC curve
predict.bagEarth
Predicted values based on bagged Earth and FDA models
resampleSummary
Summary of resampled performance estimates
histogram.train
Lattice functions for plotting resampling results