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caret (version 6.0-58)
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
160,352
Version
6.0-58
License
GPL (>= 2)
Issues
172
Pull Requests
6
Stars
1,586
Forks
630
Repository
https://github.com/topepo/caret/
Maintainer
Max Kuhn
Last Published
October 22nd, 2015
Functions in caret (6.0-58)
Search functions
findCorrelation
Determine highly correlated variables
bagEarth
Bagged Earth
lattice.rfe
Lattice functions for plotting resampling results of recursive feature selection
nullModel
Fit a simple, non-informative model
as.table.confusionMatrix
Save Confusion Table Results
pottery
Pottery from Pre-Classical Sites in Italy
plot.rfe
Plot RFE Performance Profiles
sbfControl
Control Object for Selection By Filtering (SBF)
oneSE
Selecting tuning Parameters
spatialSign
Compute the multivariate spatial sign
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
BloodBrain
Blood Brain Barrier Data
confusionMatrix
Create a confusion matrix
BoxCoxTrans.default
Box-Cox and Exponential Transformations
dummyVars
Create A Full Set of Dummy Variables
avNNet.default
Neural Networks Using Model Averaging
getSamplingInfo
Get sampling info from a train model
lift
Lift Plot
downSample
Down- and Up-Sampling Imbalanced Data
GermanCredit
German Credit Data
bag.default
A General Framework For Bagging
panel.needle
Needle Plot Lattice Panel
predictors
List predictors used in the model
dhfr
Dihydrofolate Reductase Inhibitors Data
classDist
Compute and predict the distances to class centroids
confusionMatrix.train
Estimate a Resampled Confusion Matrix
gafs.default
Genetic algorithm feature selection
plot.gafs
Plot Method for the gafs and safs Classes
caretFuncs
Backwards Feature Selection Helper Functions
index2vec
Convert indicies to a binary vector
resampleHist
Plot the resampling distribution of the model statistics
icr.formula
Independent Component Regression
diff.resamples
Inferential Assessments About Model Performance
knnreg
k-Nearest Neighbour Regression
predict.train
Extract predictions and class probabilities from train objects
oil
Fatty acid composition of commercial oils
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
calibration
Probability Calibration Plot
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
postResample
Calculates performance across resamples
plot.varImp.train
Plotting variable importance measures
maxDissim
Maximum Dissimilarity Sampling
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
knn3
k-Nearest Neighbour Classification
resampleSummary
Summary of resampled performance estimates
histogram.train
Lattice functions for plotting resampling results
predict.bagEarth
Predicted values based on bagged Earth and FDA models
plot.train
Plot Method for the train Class
dotPlot
Create a dotplot of variable importance values
print.confusionMatrix
Print method for confusionMatrix
prcomp.resamples
Principal Components Analysis of Resampling Results
format.bagEarth
Format 'bagEarth' objects
update.train
Update or Re-fit a Model
predict.gafs
Predict new samples
safsControl
Control parameters for GA and SA feature selection
panel.lift2
Lattice Panel Functions for Lift Plots
safs.default
Simulated annealing feature selection
tecator
Fat, Water and Protein Content of Meat Samples
caretSBF
Selection By Filtering (SBF) Helper Functions
findLinearCombos
Determine linear combinations in a matrix
cars
Kelly Blue Book resale data for 2005 model year GM cars
segmentationData
Cell Body Segmentation
summary.bagEarth
Summarize a bagged earth or FDA fit
sbf
Selection By Filtering (SBF)
predict.knn3
Predictions from k-Nearest Neighbors
varImp.gafs
Variable importances for GAs and SAs
twoClassSim
Simulation Functions
print.train
Print Method for the train Class
var_seq
Sequences of Variables for Tuning
rfe
Backwards Feature Selection
pcaNNet.default
Neural Networks with a Principal Component Step
safs_initial
Ancillary simulated annealing functions
nearZeroVar
Identification of near zero variance predictors
sensitivity
Calculate sensitivity, specificity and predictive values
bagFDA
Bagged FDA
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
modelLookup
Tools for Models Available in
train
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
train_model_list
A List of Available Models in train
preProcess
Pre-Processing of Predictors
createDataPartition
Data Splitting functions
plotClassProbs
Plot Predicted Probabilities in Classification Models
rfeControl
Controlling the Feature Selection Algorithms
update.safs
Update or Re-fit a SA or GA Model
trainControl
Control parameters for train
filterVarImp
Calculation of filter-based variable importance
varImp
Calculation of variable importance for regression and classification models
caret-internal
Internal Functions
resamples
Collation and Visualization of Resampling Results
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
gafs_initial
Ancillary genetic algorithm functions
cox2
COX-2 Activity Data
train
Fit Predictive Models over Different Tuning Parameters