caret v6.0-41

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by Max Kuhn

Classification and Regression Training

Misc functions for training and plotting classification and regression models

Functions in caret

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