caret v6.0-83

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Classification and Regression Training

Misc functions for training and plotting classification and regression models.

Functions in caret

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

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caret.Rmd
train_algo.png
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