Rdocumentation
powered by
Learn R Programming
⚠️
There's a newer version (7.0-1) of this package.
Take me there.
caret (version 4.05)
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
163,965
Version
4.05
License
GPL-2
Maintainer
Max Kuhn
Last Published
December 10th, 2024
Functions in caret (4.05)
Search all functions
print.train
Print Method for the train Class
format.bagEarth
Format 'bagEarth' objects
predictors
List predictors used in the model
Alternate Affy Gene Expression Summary Methods.
Generate Expression Values from Probes
summary.bagEarth
Summarize a bagged earth or FDA fit
resampleSummary
Summary of resampled performance estimates
confusionMatrix
Create a confusion matrix
plotClassProbs
Plot Predicted Probabilities in Classification Models
createDataPartition
Data Splitting functions
caret-internal
Internal Functions
filterVarImp
Calculation of filter-based variable importance
BloodBrain
Blood Brain Barrier Data
oil
Fatty acid composition of commercial oils
findCorrelation
Determine highly correlated variables
normalize2Reference
Quantile Normalize Columns of a Matrix Based on a Reference Distribution
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
predict.train
Extract predictions and class probabilities from train objects
nearZeroVar
Identification of near zero variance predictors
cox2
COX-2 Activity Data
normalize.AffyBatch.normalize2Reference
Quantile Normalization to a Reference Distribution
pottery
Pottery from Pre-Classical Sites in Italy
plot.varImp.train
Plotting variable importance measures
predict.bagEarth
Predicted values based on bagged Earth and FDA models
print.confusionMatrix
Print method for confusionMatrix
sensitivity
Calculate sensitivity, specificity and predictive values
dotPlot
Create a dotplot of variable importance values
spatialSign
Compute the multivariate spatial sign
trainControl
Control parameters for train
varImp
Calculation of variable importance for regression and classification models
resampleHist
Plot the resampling distribution of the model statistics
histogram.train
Lattice functions for plotting resampling results
preProcess
Pre-Processing of Predictors
plot.train
Plot Method for the train Class
bagEarth
Bagged Earth
applyProcessing
Data Processing on Predictor Variables (Deprecated)
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
maxDissim
Maximum Dissimilarity Sampling
predict.knn3
Predictions from k-Nearest Neighbors
roc
Compute the points for an ROC curve
plsda
Partial Least Squares Discriminant Analysis
train
Fit Predictive Models over Different Tuning Parameters
oneSE
Selecting tuning Parameters
tecator
Fat, Water and Protein Content of Maat Samples
aucRoc
Compute the area under an ROC curve
findLinearCombos
Determine linear combinations in a matrix
createGrid
Tuning Parameter Grid
panel.needle
Needle Plot Lattice Panel
bagFDA
Bagged FDA
postResample
Calculates performance across resamples
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
as.table.confusionMatrix
Save Confusion Table Results
pcaNNet.default
Neural Networks with a Principal Component Step
knn3
k-Nearest Neighbour Classification