caret v6.0-70


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