Rdocumentation
powered by
Learn R Programming
⚠️
There's a newer version (7.0-1) of this package.
Take me there.
caret (version 6.0-62)
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
231,168
Version
6.0-62
License
GPL (>= 2)
Issues
186
Pull Requests
25
Stars
1,650
Forks
628
Repository
https://github.com/topepo/caret/
Maintainer
Max Kuhn
Last Published
November 23rd, 2015
Functions in caret (6.0-62)
Search all functions
BloodBrain
Blood Brain Barrier Data
calibration
Probability Calibration Plot
dotPlot
Create a dotplot of variable importance values
gafs_initial
Ancillary genetic algorithm functions
knnreg
k-Nearest Neighbour Regression
learing_curve_dat
Create Data to Plot a Learning Curve
index2vec
Convert indicies to a binary vector
classDist
Compute and predict the distances to class centroids
rfe
Backwards Feature Selection
cars
Kelly Blue Book resale data for 2005 model year GM cars
oneSE
Selecting tuning Parameters
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
rfeControl
Controlling the Feature Selection Algorithms
bag.default
A General Framework For Bagging
as.table.confusionMatrix
Save Confusion Table Results
predict.train
Extract predictions and class probabilities from train objects
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
varImp
Calculation of variable importance for regression and classification models
update.train
Update or Re-fit a Model
predictors
List predictors used in the model
findCorrelation
Determine highly correlated variables
predict.knn3
Predictions from k-Nearest Neighbors
predict.bagEarth
Predicted values based on bagged Earth and FDA models
varImp.gafs
Variable importances for GAs and SAs
summary.bagEarth
Summarize a bagged earth or FDA fit
update.safs
Update or Re-fit a SA or GA Model
panel.lift2
Lattice Panel Functions for Lift Plots
diff.resamples
Inferential Assessments About Model Performance
cox2
COX-2 Activity Data
preProcess
Pre-Processing of Predictors
safs_initial
Ancillary simulated annealing functions
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
pottery
Pottery from Pre-Classical Sites in Italy
twoClassSim
Simulation Functions
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
maxDissim
Maximum Dissimilarity Sampling
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
predict.gafs
Predict new samples
tecator
Fat, Water and Protein Content of Meat Samples
resampleHist
Plot the resampling distribution of the model statistics
resamples
Collation and Visualization of Resampling Results
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
segmentationData
Cell Body Segmentation
BoxCoxTrans.default
Box-Cox and Exponential Transformations
modelLookup
Tools for Models Available in
train
lift
Lift Plot
oil
Fatty acid composition of commercial oils
safs.default
Simulated annealing feature selection
var_seq
Sequences of Variables for Tuning
caret-internal
Internal Functions
prcomp.resamples
Principal Components Analysis of Resampling Results
confusionMatrix.train
Estimate a Resampled Confusion Matrix
plot.train
Plot Method for the train Class
print.confusionMatrix
Print method for confusionMatrix
downSample
Down- and Up-Sampling Imbalanced Data
sbf
Selection By Filtering (SBF)
knn3
k-Nearest Neighbour Classification
gafs.default
Genetic algorithm feature selection
plot.rfe
Plot RFE Performance Profiles
caretSBF
Selection By Filtering (SBF) Helper Functions
spatialSign
Compute the multivariate spatial sign
resampleSummary
Summary of resampled performance estimates
icr.formula
Independent Component Regression
safsControl
Control parameters for GA and SA feature selection
filterVarImp
Calculation of filter-based variable importance
plot.gafs
Plot Method for the gafs and safs Classes
pcaNNet.default
Neural Networks with a Principal Component Step
plot.varImp.train
Plotting variable importance measures
plotClassProbs
Plot Predicted Probabilities in Classification Models
avNNet.default
Neural Networks Using Model Averaging
nearZeroVar
Identification of near zero variance predictors
bagFDA
Bagged FDA
dummyVars
Create A Full Set of Dummy Variables
confusionMatrix
Create a confusion matrix
sensitivity
Calculate sensitivity, specificity and predictive values
postResample
Calculates performance across resamples
panel.needle
Needle Plot Lattice Panel
format.bagEarth
Format 'bagEarth' objects
sbfControl
Control Object for Selection By Filtering (SBF)
bagEarth
Bagged Earth
createDataPartition
Data Splitting functions
getSamplingInfo
Get sampling info from a train model
GermanCredit
German Credit Data
trainControl
Control parameters for train
nullModel
Fit a simple, non-informative model
caretFuncs
Backwards Feature Selection Helper Functions
train_model_list
A List of Available Models in train
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
print.train
Print Method for the train Class
histogram.train
Lattice functions for plotting resampling results
dhfr
Dihydrofolate Reductase Inhibitors Data
findLinearCombos
Determine linear combinations in a matrix
train
Fit Predictive Models over Different Tuning Parameters