/usr/lib/R/site-library/caret/INDEX is in r-cran-caret 6.0-78+dfsg1-1.
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The actual contents of the file can be viewed below.
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BoxCoxTrans Box-Cox and Exponential Transformations
GermanCredit German Credit Data
SLC14_1 Simulation Functions
Sacramento Sacramento CA Home Prices
as.matrix.confusionMatrix
Confusion matrix as a table
avNNet Neural Networks Using Model Averaging
bag A General Framework For Bagging
bagEarth Bagged Earth
bagFDA Bagged FDA
calibration Probability Calibration Plot
caretSBF Selection By Filtering (SBF) Helper Functions
cars Kelly Blue Book resale data for 2005 model year
GM cars
classDist Compute and predict the distances to class
centroids
confusionMatrix Create a confusion matrix
confusionMatrix.train Estimate a Resampled Confusion Matrix
cox2 COX-2 Activity Data
createDataPartition Data Splitting functions
defaultSummary Calculates performance across resamples
densityplot.rfe Lattice functions for plotting resampling
results of recursive feature selection
dhfr Dihydrofolate Reductase Inhibitors Data
diff.resamples Inferential Assessments About Model Performance
dotPlot Create a dotplot of variable importance values
dotplot.diff.resamples
Lattice Functions for Visualizing Resampling
Differences
downSample Down- and Up-Sampling Imbalanced Data
dummyVars Create A Full Set of Dummy Variables
extractPrediction Extract predictions and class probabilities
from train objects
featurePlot Wrapper for Lattice Plotting of Predictor
Variables
filterVarImp Calculation of filter-based variable importance
findCorrelation Determine highly correlated variables
findLinearCombos Determine linear combinations in a matrix
format.bagEarth Format 'bagEarth' objects
gafs.default Genetic algorithm feature selection
gafsControl Control parameters for GA and SA feature
selection
gafs_initial Ancillary genetic algorithm functions
getSamplingInfo Get sampling info from a train model
ggplot.rfe Plot RFE Performance Profiles
ggplot.train Plot Method for the train Class
histogram.train Lattice functions for plotting resampling
results
icr.formula Independent Component Regression
index2vec Convert indicies to a binary vector
knn3 k-Nearest Neighbour Classification
knnreg k-Nearest Neighbour Regression
learing_curve_dat Create Data to Plot a Learning Curve
lift Lift Plot
maxDissim Maximum Dissimilarity Sampling
mdrr Multidrug Resistance Reversal (MDRR) Agent Data
modelLookup Tools for Models Available in 'train'
nearZeroVar Identification of near zero variance predictors
negPredValue Calculate sensitivity, specificity and
predictive values
nullModel Fit a simple, non-informative model
oil Fatty acid composition of commercial oils
oneSE Selecting tuning Parameters
panel.lift2 Lattice Panel Functions for Lift Plots
panel.needle Needle Plot Lattice Panel
pcaNNet Neural Networks with a Principal Component Step
pickSizeBest Backwards Feature Selection Helper Functions
plot.gafs Plot Method for the gafs and safs Classes
plot.varImp.train Plotting variable importance measures
plotClassProbs Plot Predicted Probabilities in Classification
Models
plotObsVsPred Plot Observed versus Predicted Results in
Regression and Classification Models
plsda Partial Least Squares and Sparse Partial Least
Squares Discriminant Analysis
pottery Pottery from Pre-Classical Sites in Italy
prcomp.resamples Principal Components Analysis of Resampling
Results
preProcess Pre-Processing of Predictors
predict.bagEarth Predicted values based on bagged Earth and FDA
models
predict.gafs Predict new samples
predict.knn3 Predictions from k-Nearest Neighbors
predict.knnreg Predictions from k-Nearest Neighbors Regression
Model
predictors List predictors used in the model
print.confusionMatrix Print method for confusionMatrix
print.train Print Method for the train Class
recall Calculate recall, precision and F values
resampleHist Plot the resampling distribution of the model
statistics
resampleSummary Summary of resampled performance estimates
resamples Collation and Visualization of Resampling
Results
rfe Backwards Feature Selection
rfeControl Controlling the Feature Selection Algorithms
safs Simulated annealing feature selection
safs_initial Ancillary simulated annealing functions
sbf Selection By Filtering (SBF)
sbfControl Control Object for Selection By Filtering (SBF)
scat Morphometric Data on Scat
segmentationData Cell Body Segmentation
spatialSign Compute the multivariate spatial sign
summary.bagEarth Summarize a bagged earth or FDA fit
tecator Fat, Water and Protein Content of Meat Samples
thresholder Generate Data to Choose a Probability Threshold
train Fit Predictive Models over Different Tuning
Parameters
trainControl Control parameters for train
train_model_list A List of Available Models in train
update.safs Update or Re-fit a SA or GA Model
update.train Update or Re-fit a Model
varImp Calculation of variable importance for
regression and classification models
varImp.gafs Variable importances for GAs and SAs
var_seq Sequences of Variables for Tuning
xyplot.resamples Lattice Functions for Visualizing Resampling
Results
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