caret v6.0-47

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