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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 |