Rdocumentation
powered by
Learn R Programming
⚠️
There's a newer version (7.0-1) of this package.
Take me there.
caret (version 6.0-29)
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
6.0-29
License
GPL-2
Maintainer
Max Kuhn
Last Published
May 28th, 2014
Functions in caret (6.0-29)
Search all functions
calibration
Probability Calibration Plot
BoxCoxTrans.default
Box-Cox and Exponential Transformations
classDist
Compute and predict the distances to class centroids
plot.varImp.train
Plotting variable importance measures
dhfr
Dihydrofolate Reductase Inhibitors Data
modelLookup
Tools for Models Available in
train
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
confusionMatrix.train
Estimate a Resampled Confusion Matrix
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
BloodBrain
Blood Brain Barrier Data
cox2
COX-2 Activity Data
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
diff.resamples
Inferential Assessments About Model Performance
plot.train
Plot Method for the train Class
caret-internal
Internal Functions
panel.needle
Needle Plot Lattice Panel
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
findCorrelation
Determine highly correlated variables
histogram.train
Lattice functions for plotting resampling results
pcaNNet.default
Neural Networks with a Principal Component Step
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
lift
Lift Plot
nearZeroVar
Identification of near zero variance predictors
confusionMatrix
Create a confusion matrix
dotPlot
Create a dotplot of variable importance values
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
downSample
Down- and Up-Sampling Imbalanced Data
twoClassSim
Two-Class Simulations
dummyVars
Create A Full Set of Dummy Variables
rfe
Backwards Feature Selection
postResample
Calculates performance across resamples
resampleHist
Plot the resampling distribution of the model statistics
predict.bagEarth
Predicted values based on bagged Earth and FDA models
oil
Fatty acid composition of commercial oils
predict.knn3
Predictions from k-Nearest Neighbors
summary.bagEarth
Summarize a bagged earth or FDA fit
knn3
k-Nearest Neighbour Classification
resampleSummary
Summary of resampled performance estimates
train_model_list
A List of Available Models in train
sbf
Selection By Filtering (SBF)
spatialSign
Compute the multivariate spatial sign
trainControl
Control parameters for train
avNNet.default
Neural Networks Using Model Averaging
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
as.table.confusionMatrix
Save Confusion Table Results
varImp
Calculation of variable importance for regression and classification models
bagFDA
Bagged FDA
sensitivity
Calculate sensitivity, specificity and predictive values
sbfControl
Control Object for Selection By Filtering (SBF)
preProcess
Pre-Processing of Predictors
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
print.train
Print Method for the train Class
nullModel
Fit a simple, non-informative model
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
bagEarth
Bagged Earth
plot.rfe
Plot RFE Performance Profiles
findLinearCombos
Determine linear combinations in a matrix
resamples
Collation and Visualization of Resampling Results
knnreg
k-Nearest Neighbour Regression
plotClassProbs
Plot Predicted Probabilities in Classification Models
oneSE
Selecting tuning Parameters
print.confusionMatrix
Print method for confusionMatrix
tecator
Fat, Water and Protein Content of Meat Samples
maxDissim
Maximum Dissimilarity Sampling
icr.formula
Independent Component Regression
pottery
Pottery from Pre-Classical Sites in Italy
cars
Kelly Blue Book resale data for 2005 model year GM cars
prcomp.resamples
Principal Components Analysis of Resampling Results
segmentationData
Cell Body Segmentation
panel.lift2
Lattice Panel Functions for Lift Plots
bag.default
A General Framework For Bagging
format.bagEarth
Format 'bagEarth' objects
predict.train
Extract predictions and class probabilities from train objects
caretSBF
Selection By Filtering (SBF) Helper Functions
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
caretFuncs
Backwards Feature Selection Helper Functions
rfeControl
Controlling the Feature Selection Algorithms
predictors
List predictors used in the model
filterVarImp
Calculation of filter-based variable importance
createDataPartition
Data Splitting functions
GermanCredit
German Credit Data
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
update.train
Update or Re-fit a Model
train
Fit Predictive Models over Different Tuning Parameters