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caret (version 6.0-85)

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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121,196

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6.0-85

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GPL (>= 2)

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Last Published

January 7th, 2020

Functions in caret (6.0-85)

as.matrix.confusionMatrix

Confusion matrix as a table
GermanCredit

German Credit Data
avNNet

Neural Networks Using Model Averaging
pickSizeBest

Backwards Feature Selection Helper Functions
caret-internal

Internal Functions
createDataPartition

Data Splitting functions
densityplot.rfe

Lattice functions for plotting resampling results of recursive feature selection
classDist

Compute and predict the distances to class centroids
confusionMatrix

Create a confusion matrix
Sacramento

Sacramento CA Home Prices
findCorrelation

Determine highly correlated variables
cars

Kelly Blue Book resale data for 2005 model year GM cars
caretSBF

Selection By Filtering (SBF) Helper Functions
dhfr

Dihydrofolate Reductase Inhibitors Data
dotPlot

Create a dotplot of variable importance values
dotplot.diff.resamples

Lattice Functions for Visualizing Resampling Differences
featurePlot

Wrapper for Lattice Plotting of Predictor Variables
diff.resamples

Inferential Assessments About Model Performance
findLinearCombos

Determine linear combinations in a matrix
knnreg

k-Nearest Neighbour Regression
icr.formula

Independent Component Regression
learning_curve_dat

Create Data to Plot a Learning Curve
filterVarImp

Calculation of filter-based variable importance
histogram.train

Lattice functions for plotting resampling results
gafs.default

Genetic algorithm feature selection
format.bagEarth

Format 'bagEarth' objects
index2vec

Convert indicies to a binary vector
cox2

COX-2 Activity Data
confusionMatrix.train

Estimate a Resampled Confusion Matrix
knn3

k-Nearest Neighbour Classification
getSamplingInfo

Get sampling info from a train model
downSample

Down- and Up-Sampling Imbalanced Data
gafs_initial

Ancillary genetic algorithm functions
dummyVars

Create A Full Set of Dummy Variables
nullModel

Fit a simple, non-informative model
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
nearZeroVar

Identification of near zero variance predictors
train_model_list

A List of Available Models in train
maxDissim

Maximum Dissimilarity Sampling
lift

Lift Plot
oil

Fatty acid composition of commercial oils
plsda

Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
plot.gafs

Plot Method for the gafs and safs Classes
pcaNNet

Neural Networks with a Principal Component Step
panel.needle

Needle Plot Lattice Panel
plotClassProbs

Plot Predicted Probabilities in Classification Models
ggplot.train

Plot Method for the train Class
ggplot.rfe

Plot RFE Performance Profiles
defaultSummary

Calculates performance across resamples
plotObsVsPred

Plot Observed versus Predicted Results in Regression and Classification Models
pottery

Pottery from Pre-Classical Sites in Italy
prcomp.resamples

Principal Components Analysis of Resampling Results
print.confusionMatrix

Print method for confusionMatrix
predictors

List predictors used in the model
extractPrediction

Extract predictions and class probabilities from train objects
plot.varImp.train

Plotting variable importance measures
predict.gafs

Predict new samples
predict.knn3

Predictions from k-Nearest Neighbors
resampleHist

Plot the resampling distribution of the model statistics
predict.knnreg

Predictions from k-Nearest Neighbors Regression Model
resampleSummary

Summary of resampled performance estimates
rfe

Backwards Feature Selection
resamples

Collation and Visualization of Resampling Results
gafsControl

Control parameters for GA and SA feature selection
sbf

Selection By Filtering (SBF)
spatialSign

Compute the multivariate spatial sign
negPredValue

Calculate sensitivity, specificity and predictive values
rfeControl

Controlling the Feature Selection Algorithms
scat

Morphometric Data on Scat
segmentationData

Cell Body Segmentation
sbfControl

Control Object for Selection By Filtering (SBF)
safs

Simulated annealing feature selection
predict.bagEarth

Predicted values based on bagged Earth and FDA models
preProcess

Pre-Processing of Predictors
update.train

Update or Re-fit a Model
update.safs

Update or Re-fit a SA or GA Model
print.train

Print Method for the train Class
varImp

Calculation of variable importance for regression and classification models
recall

Calculate recall, precision and F values
trainControl

Control parameters for train
safs_initial

Ancillary simulated annealing functions
summary.bagEarth

Summarize a bagged earth or FDA fit
tecator

Fat, Water and Protein Content of Meat Samples
train

Fit Predictive Models over Different Tuning Parameters
SLC14_1

Simulation Functions
var_seq

Sequences of Variables for Tuning
xyplot.resamples

Lattice Functions for Visualizing Resampling Results
thresholder

Generate Data to Choose a Probability Threshold
varImp.gafs

Variable importances for GAs and SAs
bag

A General Framework For Bagging
BloodBrain

Blood Brain Barrier Data
BoxCoxTrans

Box-Cox and Exponential Transformations
bagFDA

Bagged FDA
calibration

Probability Calibration Plot
bagEarth

Bagged Earth