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caret (version 6.0-81)
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
208,749
Version
6.0-81
License
GPL (>= 2)
Issues
178
Pull Requests
7
Stars
1,614
Forks
632
Repository
https://github.com/topepo/caret/
Maintainer
Max Kuhn
Last Published
November 20th, 2018
Functions in caret (6.0-81)
Search all functions
GermanCredit
German Credit Data
classDist
Compute and predict the distances to class centroids
BloodBrain
Blood Brain Barrier Data
BoxCoxTrans
Box-Cox and Exponential Transformations
confusionMatrix
Create a confusion matrix
confusionMatrix.train
Estimate a Resampled Confusion Matrix
cox2
COX-2 Activity Data
downSample
Down- and Up-Sampling Imbalanced Data
dotPlot
Create a dotplot of variable importance values
dummyVars
Create A Full Set of Dummy Variables
knnreg
k-Nearest Neighbour Regression
learing_curve_dat
Create Data to Plot a Learning Curve
bag
A General Framework For Bagging
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling Differences
histogram.train
Lattice functions for plotting resampling results
bagEarth
Bagged Earth
lift
Lift Plot
caret-internal
Internal Functions
maxDissim
Maximum Dissimilarity Sampling
icr.formula
Independent Component Regression
pickSizeBest
Backwards Feature Selection Helper Functions
ggplot.train
Plot Method for the train Class
mdrr
Multidrug Resistance Reversal (MDRR) Agent Data
pottery
Pottery from Pre-Classical Sites in Italy
plot.varImp.train
Plotting variable importance measures
findCorrelation
Determine highly correlated variables
findLinearCombos
Determine linear combinations in a matrix
prcomp.resamples
Principal Components Analysis of Resampling Results
print.train
Print Method for the train Class
gafs_initial
Ancillary genetic algorithm functions
bagFDA
Bagged FDA
modelLookup
Tools for Models Available in
train
recall
Calculate recall, precision and F values
getSamplingInfo
Get sampling info from a train model
scat
Morphometric Data on Scat
segmentationData
Cell Body Segmentation
xyplot.resamples
Lattice Functions for Visualizing Resampling Results
var_seq
Sequences of Variables for Tuning
plot.gafs
Plot Method for the gafs and safs Classes
ggplot.rfe
Plot RFE Performance Profiles
calibration
Probability Calibration Plot
createDataPartition
Data Splitting functions
densityplot.rfe
Lattice functions for plotting resampling results of recursive feature selection
train_model_list
A List of Available Models in train
dhfr
Dihydrofolate Reductase Inhibitors Data
nearZeroVar
Identification of near zero variance predictors
plsda
Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
as.matrix.confusionMatrix
Confusion matrix as a table
defaultSummary
Calculates performance across resamples
caretSBF
Selection By Filtering (SBF) Helper Functions
avNNet
Neural Networks Using Model Averaging
predict.gafs
Predict new samples
cars
Kelly Blue Book resale data for 2005 model year GM cars
featurePlot
Wrapper for Lattice Plotting of Predictor Variables
filterVarImp
Calculation of filter-based variable importance
preProcess
Pre-Processing of Predictors
diff.resamples
Inferential Assessments About Model Performance
index2vec
Convert indicies to a binary vector
format.bagEarth
Format 'bagEarth' objects
knn3
k-Nearest Neighbour Classification
gafs.default
Genetic algorithm feature selection
resampleHist
Plot the resampling distribution of the model statistics
predict.knn3
Predictions from k-Nearest Neighbors
predict.bagEarth
Predicted values based on bagged Earth and FDA models
resampleSummary
Summary of resampled performance estimates
nullModel
Fit a simple, non-informative model
oil
Fatty acid composition of commercial oils
rfeControl
Controlling the Feature Selection Algorithms
oneSE
Selecting tuning Parameters
plotObsVsPred
Plot Observed versus Predicted Results in Regression and Classification Models
sbf
Selection By Filtering (SBF)
plotClassProbs
Plot Predicted Probabilities in Classification Models
safs
Simulated annealing feature selection
negPredValue
Calculate sensitivity, specificity and predictive values
panel.lift2
Lattice Panel Functions for Lift Plots
sbfControl
Control Object for Selection By Filtering (SBF)
panel.needle
Needle Plot Lattice Panel
spatialSign
Compute the multivariate spatial sign
update.safs
Update or Re-fit a SA or GA Model
pcaNNet
Neural Networks with a Principal Component Step
predictors
List predictors used in the model
update.train
Update or Re-fit a Model
predict.knnreg
Predictions from k-Nearest Neighbors Regression Model
print.confusionMatrix
Print method for confusionMatrix
gafsControl
Control parameters for GA and SA feature selection
safs_initial
Ancillary simulated annealing functions
summary.bagEarth
Summarize a bagged earth or FDA fit
tecator
Fat, Water and Protein Content of Meat Samples
extractPrediction
Extract predictions and class probabilities from train objects
varImp
Calculation of variable importance for regression and classification models
resamples
Collation and Visualization of Resampling Results
rfe
Backwards Feature Selection
varImp.gafs
Variable importances for GAs and SAs
thresholder
Generate Data to Choose a Probability Threshold
train
Fit Predictive Models over Different Tuning Parameters
trainControl
Control parameters for train
SLC14_1
Simulation Functions
Sacramento
Sacramento CA Home Prices