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caret (version 6.0-86)
Classification and Regression Training
Description
Misc functions for training and plotting classification and regression models.
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Install
install.packages('caret')
Monthly Downloads
163,965
Version
6.0-86
License
GPL (>= 2)
Issues
186
Pull Requests
25
Stars
1,650
Forks
628
Repository
https://github.com/topepo/caret/
Maintainer
Max Kuhn
Last Published
March 20th, 2020
Functions in caret (6.0-86)
Search all functions
avNNet
Neural Networks Using Model Averaging
Sacramento
Sacramento CA Home Prices
BloodBrain
Blood Brain Barrier Data
bagFDA
Bagged FDA
GermanCredit
German Credit Data
bag
A General Framework For Bagging
calibration
Probability Calibration Plot
createDataPartition
Data Splitting functions
bagEarth
Bagged Earth
as.matrix.confusionMatrix
Confusion matrix as a table
BoxCoxTrans
Box-Cox and Exponential Transformations
cars
Kelly Blue Book resale data for 2005 model year GM cars
caret-internal
Internal Functions
classDist
Compute and predict the distances to class centroids
confusionMatrix.train
Estimate a Resampled Confusion Matrix
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
caretSBF
Selection By Filtering (SBF) Helper Functions
dotPlot
Create a dotplot of variable importance values
densityplot.rfe
Lattice functions for plotting resampling results of recursive feature selection
downSample
Down- and Up-Sampling Imbalanced Data
confusionMatrix
Create a confusion matrix
cox2
COX-2 Activity Data
format.bagEarth
Format 'bagEarth' objects
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
diff.resamples
Inferential Assessments About Model Performance
dummyVars
Create A Full Set of Dummy Variables
dhfr
Dihydrofolate Reductase Inhibitors Data
filterVarImp
Calculation of filter-based variable importance
index2vec
Convert indicies to a binary vector
gafs_initial
Ancillary genetic algorithm functions
pickSizeBest
Backwards Feature Selection Helper Functions
getSamplingInfo
Get sampling info from a train model
findLinearCombos
Determine linear combinations in a matrix
gafs.default
Genetic algorithm feature selection
knn3
k-Nearest Neighbour Classification
histogram.train
Lattice functions for plotting resampling results
knnreg
k-Nearest Neighbour Regression
oneSE
Selecting tuning Parameters
icr.formula
Independent Component Regression
plot.gafs
Plot Method for the gafs and safs Classes
train_model_list
A List of Available Models in train
lift
Lift Plot
modelLookup
Tools for Models Available in
train
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
findCorrelation
Determine highly correlated variables
maxDissim
Maximum Dissimilarity Sampling
nearZeroVar
Identification of near zero variance predictors
learning_curve_dat
Create Data to Plot a Learning Curve
plotClassProbs
Plot Predicted Probabilities in Classification Models
plot.varImp.train
Plotting variable importance measures
panel.needle
Needle Plot Lattice Panel
ggplot.rfe
Plot RFE Performance Profiles
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
ggplot.train
Plot Method for the train Class
oil
Fatty acid composition of commercial oils
panel.lift2
Lattice Panel Functions for Lift Plots
nullModel
Fit a simple, non-informative model
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
extractPrediction
Extract predictions and class probabilities from train objects
preProcess
Pre-Processing of Predictors
safs_initial
Ancillary simulated annealing functions
predict.bagEarth
Predicted values based on bagged Earth and FDA models
pcaNNet
Neural Networks with a Principal Component Step
rfe
Backwards Feature Selection
pottery
Pottery from Pre-Classical Sites in Italy
rfeControl
Controlling the Feature Selection Algorithms
prcomp.resamples
Principal Components Analysis of Resampling Results
defaultSummary
Calculates performance across resamples
summary.bagEarth
Summarize a bagged earth or FDA fit
predict.gafs
Predict new samples
gafsControl
Control parameters for GA and SA feature selection
predict.knn3
Predictions from k-Nearest Neighbors
resampleHist
Plot the resampling distribution of the model statistics
resamples
Collation and Visualization of Resampling Results
resampleSummary
Summary of resampled performance estimates
print.train
Print Method for the train Class
recall
Calculate recall, precision and F values
safs
Simulated annealing feature selection
sbfControl
Control Object for Selection By Filtering (SBF)
sbf
Selection By Filtering (SBF)
predictors
List predictors used in the model
print.confusionMatrix
Print method for confusionMatrix
tecator
Fat, Water and Protein Content of Meat Samples
segmentationData
Cell Body Segmentation
thresholder
Generate Data to Choose a Probability Threshold
var_seq
Sequences of Variables for Tuning
update.safs
Update or Re-fit a SA or GA Model
scat
Morphometric Data on Scat
trainControl
Control parameters for train
negPredValue
Calculate sensitivity, specificity and predictive values
SLC14_1
Simulation Functions
spatialSign
Compute the multivariate spatial sign
train
Fit Predictive Models over Different Tuning Parameters
varImp
Calculation of variable importance for regression and classification models
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
varImp.gafs
Variable importances for GAs and SAs
update.train
Update or Re-fit a Model