Implementation of the Kernel-based Orthogonal Projections to Latent Structures (K-OPLS) method


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Documentation for package `kopls' version 1.0.3

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kopls-package Kernel-based orthogonal projections to latent structures (K-OPLS)
kopls Kernel-based orthogonal projections to latent structures (K-OPLS)
koplsBasicClassify Classification rule based on a fixed threshold
koplsCenterKTeTe Centering function for the test kernel
koplsCenterKTeTr Centering function for the hybrid test/training kernel
koplsCenterKTrTr Centering function for the training kernel
koplsConfusionMatrix Calculation of confusion matrix
koplsCrossValSet Generate training/test observations for cross-validation
koplsCV K-OPLS cross-validation
koplsDemo K-OPLS demonstration procedure
koplsDummy Convertion of integer vector to dummy matrix
koplsKernel Kernel construction method
koplsMaxClassify Classification rule based on the maximum class belonging
koplsModel K-OPLS model training
koplsPlotCVDiagnostics Overview plot of cross-validation results
koplsPlotModelDiagnostics Overview of model training results
koplsPlotScores Plots scores from trained K-OPLS models
koplsPlotSensSpec Plots sensitivity and specificity results from cross-validation
koplsPredict Prediction of new samples from a K-OPLS model
koplsReDummy Reconstruct class vector
koplsRescale Matrix scaling based on pre-defined parameters
koplsScale Matrix scaling function
koplsScaleApply Apply matrix scaling
koplsSensSpec Sensitivity and specificity calculations for classification