caret v6.0-72

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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
caret-internal Internal Functions
caretSBF Selection By Filtering (SBF) Helper Functions
calibration Probability Calibration Plot
avNNet Neural Networks Using Model Averaging
BoxCoxTrans Box-Cox and Exponential Transformations
as.matrix.confusionMatrix Confusion matrix as a table
pickSizeBest Backwards Feature Selection Helper Functions
bagFDA Bagged FDA
diff.resamples Inferential Assessments About Model Performance
downSample Down- and Up-Sampling Imbalanced Data
createDataPartition Data Splitting functions
dotplot.diff.resamples Lattice Functions for Visualizing Resampling Differences
dotPlot Create a dotplot of variable importance values
densityplot.rfe Lattice functions for plotting resampling results of recursive feature selection
classDist Compute and predict the distances to class centroids
confusionMatrix.train Estimate a Resampled Confusion Matrix
dummyVars Create A Full Set of Dummy Variables
featurePlot Wrapper for Lattice Plotting of Predictor Variables
gafs_initial Ancillary genetic algorithm functions
histogram.train Lattice functions for plotting resampling results
GermanCredit German Credit Data
getSamplingInfo Get sampling info from a train model
filterVarImp Calculation of filter-based variable importance
findLinearCombos Determine linear combinations in a matrix
gafs.default Genetic algorithm feature selection
format.bagEarth Format 'bagEarth' objects
icr.formula Independent Component Regression
findCorrelation Determine highly correlated variables
knn3 k-Nearest Neighbour Classification
lift Lift Plot
modelLookup Tools for Models Available in train
knnreg k-Nearest Neighbour Regression
index2vec Convert indicies to a binary vector
maxDissim Maximum Dissimilarity Sampling
learing_curve_dat Create Data to Plot a Learning Curve
train_model_list A List of Available Models in train
nearZeroVar Identification of near zero variance predictors
nullModel Fit a simple, non-informative model
ggplot.train Plot Method for the train Class
plotClassProbs Plot Predicted Probabilities in Classification Models
panel.needle Needle Plot Lattice Panel
oneSE Selecting tuning Parameters
plot.varImp.train Plotting variable importance measures
panel.lift2 Lattice Panel Functions for Lift Plots
plot.gafs Plot Method for the gafs and safs Classes
ggplot.rfe Plot RFE Performance Profiles
pcaNNet Neural Networks with a Principal Component Step
plotObsVsPred Plot Observed versus Predicted Results in Regression and Classification Models
predict.knnreg Predictions from k-Nearest Neighbors Regression Model
predict.knn3 Predictions from k-Nearest Neighbors
preProcess Pre-Processing of Predictors
predict.gafs Predict new samples
predictors List predictors used in the model
predict.bagEarth Predicted values based on bagged Earth and FDA models
extractPrediction Extract predictions and class probabilities from train objects
print.confusionMatrix Print method for confusionMatrix
plsda Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
prcomp.resamples Principal Components Analysis of Resampling Results
bagEarth Bagged Earth
safs_initial Ancillary simulated annealing functions
varImp.gafs Variable importances for GAs and SAs
safs Simulated annealing feature selection
var_seq Sequences of Variables for Tuning
bag A General Framework For Bagging
rfe Backwards Feature Selection
rfeControl Controlling the Feature Selection Algorithms
sbfControl Control Object for Selection By Filtering (SBF)
spatialSign Compute the multivariate spatial sign
varImp Calculation of variable importance for regression and classification models
xyplot.resamples Lattice Functions for Visualizing Resampling Results
resamples Collation and Visualization of Resampling Results
resampleSummary Summary of resampled performance estimates
print.train Print Method for the train Class
resampleHist Plot the resampling distribution of the model statistics
update.train Update or Re-fit a Model
update.safs Update or Re-fit a SA or GA Model
trainControl Control parameters for train
SLC14_1 Simulation Functions
gafsControl Control parameters for GA and SA feature selection
sbf Selection By Filtering (SBF)
summary.bagEarth Summarize a bagged earth or FDA fit
train Fit Predictive Models over Different Tuning Parameters
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