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lsorber / neo-ls-svm

Neo LS-SVM is a modern Least-Squares Support Vector Machine implementation
MIT License
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Feature: anomaly detection with One-Class LS-SVM #15

Open lsorber opened 7 months ago

lsorber commented 7 months ago

Ideas:

  1. Allow the user to supply a target y and then apply a separating affine transform before running One-Class LS-SVM so that similarity is measured in y-separating feature space instead of the given feature space.
  2. Perhaps use the resulting OC-LS-SVM (1) to fit a robust LS-SVM by reweighting or excluding samples.

References:

  1. Least squares one-class support vector machine
  2. One-class LS-SVM with zero leave-one-out error