caret v6.0-71

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