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caret (version 6.0-82)
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
121,196
Version
6.0-82
License
GPL (>= 2)
Issues
177
Pull Requests
7
Stars
1,606
Forks
636
Repository
https://github.com/topepo/caret/
Maintainer
Max Kuhn
Last Published
March 26th, 2019
Functions in caret (6.0-82)
Search all functions
calibration
Probability Calibration Plot
classDist
Compute and predict the distances to class centroids
histogram.train
Lattice functions for plotting resampling results
nullModel
Fit a simple, non-informative model
oil
Fatty acid composition of commercial oils
icr.formula
Independent Component Regression
plotClassProbs
Plot Predicted Probabilities in Classification Models
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
safs_initial
Ancillary simulated annealing functions
gafsControl
Control parameters for GA and SA feature selection
confusionMatrix
Create a confusion matrix
caret-internal
Internal Functions
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
createDataPartition
Data Splitting functions
pickSizeBest
Backwards Feature Selection Helper Functions
findCorrelation
Determine highly correlated variables
cox2
COX-2 Activity Data
confusionMatrix.train
Estimate a Resampled Confusion Matrix
dotPlot
Create a dotplot of variable importance values
filterVarImp
Calculation of filter-based variable importance
negPredValue
Calculate sensitivity, specificity and predictive values
knnreg
k-Nearest Neighbour Regression
densityplot.rfe
Lattice functions for plotting resampling results of recursive feature selection
index2vec
Convert indicies to a binary vector
spatialSign
Compute the multivariate spatial sign
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
learning_curve_dat
Create Data to Plot a Learning Curve
downSample
Down- and Up-Sampling Imbalanced Data
dummyVars
Create A Full Set of Dummy Variables
var_seq
Sequences of Variables for Tuning
knn3
k-Nearest Neighbour Classification
caretSBF
Selection By Filtering (SBF) Helper Functions
cars
Kelly Blue Book resale data for 2005 model year GM cars
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
oneSE
Selecting tuning Parameters
panel.lift2
Lattice Panel Functions for Lift Plots
modelLookup
Tools for Models Available in
train
panel.needle
Needle Plot Lattice Panel
dhfr
Dihydrofolate Reductase Inhibitors Data
ggplot.train
Plot Method for the train Class
gafs_initial
Ancillary genetic algorithm functions
diff.resamples
Inferential Assessments About Model Performance
getSamplingInfo
Get sampling info from a train model
preProcess
Pre-Processing of Predictors
predict.bagEarth
Predicted values based on bagged Earth and FDA models
format.bagEarth
Format 'bagEarth' objects
findLinearCombos
Determine linear combinations in a matrix
lift
Lift Plot
gafs.default
Genetic algorithm feature selection
resampleHist
Plot the resampling distribution of the model statistics
pcaNNet
Neural Networks with a Principal Component Step
maxDissim
Maximum Dissimilarity Sampling
nearZeroVar
Identification of near zero variance predictors
train_model_list
A List of Available Models in train
resampleSummary
Summary of resampled performance estimates
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
defaultSummary
Calculates performance across resamples
plot.varImp.train
Plotting variable importance measures
predictors
List predictors used in the model
print.confusionMatrix
Print method for confusionMatrix
summary.bagEarth
Summarize a bagged earth or FDA fit
tecator
Fat, Water and Protein Content of Meat Samples
resamples
Collation and Visualization of Resampling Results
rfe
Backwards Feature Selection
thresholder
Generate Data to Choose a Probability Threshold
pottery
Pottery from Pre-Classical Sites in Italy
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
plot.gafs
Plot Method for the gafs and safs Classes
ggplot.rfe
Plot RFE Performance Profiles
varImp
Calculation of variable importance for regression and classification models
prcomp.resamples
Principal Components Analysis of Resampling Results
extractPrediction
Extract predictions and class probabilities from train objects
predict.gafs
Predict new samples
train
Fit Predictive Models over Different Tuning Parameters
SLC14_1
Simulation Functions
trainControl
Control parameters for train
print.train
Print Method for the train Class
predict.knn3
Predictions from k-Nearest Neighbors
varImp.gafs
Variable importances for GAs and SAs
rfeControl
Controlling the Feature Selection Algorithms
safs
Simulated annealing feature selection
sbf
Selection By Filtering (SBF)
sbfControl
Control Object for Selection By Filtering (SBF)
recall
Calculate recall, precision and F values
scat
Morphometric Data on Scat
segmentationData
Cell Body Segmentation
update.safs
Update or Re-fit a SA or GA Model
update.train
Update or Re-fit a Model
GermanCredit
German Credit Data
Sacramento
Sacramento CA Home Prices
bagFDA
Bagged FDA
BloodBrain
Blood Brain Barrier Data
BoxCoxTrans
Box-Cox and Exponential Transformations
as.matrix.confusionMatrix
Confusion matrix as a table
bag
A General Framework For Bagging
bagEarth
Bagged Earth
avNNet
Neural Networks Using Model Averaging