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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.packages('caret')

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162,548

Version

6.0-86

License

GPL (>= 2)

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Maintainer

Max Kuhn

Last Published

March 20th, 2020

Functions in caret (6.0-86)

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