caret v6.0-58

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