Robust Bichromatic Classification Using Two Lines

Erwin Glazenburg, Thijs van der Horst, Tom Peters, Bettina Speckmann, Frank Staals

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

Given two sets R and B of n points in the plane, we present efficient algorithms to find a two-line linear classifier that best separates the “red” points in R from the “blue” points in B and is robust to outliers. More precisely, we find a region WB bounded by two lines, so either a halfplane, strip, wedge, or double wedge, containing (most of) the blue points B, and few red points. Our running times vary between optimal O(n log n) up to around O(n3), depending on the type of region WB and whether we wish to minimize only red outliers, only blue outliers, or both.

Original languageEnglish
Title of host publication35th International Symposium on Algorithms and Computation (ISAAC 2024)
EditorsJulián Mestre, Anthony Wirth
PublisherDagstuhl Publishing
Pages33:1-33:14
Number of pages14
ISBN (Electronic)978-3-95977-354-6
ISBN (Print)978-3-95977-354-6
DOIs
Publication statusPublished - 4 Dec 2024

Publication series

NameLeibniz International Proceedings in Informatics, LIPIcs
Volume322
ISSN (Print)1868-8969

Bibliographical note

Publisher Copyright:
© Erwin Glazenburg, Thijs van der Horst, Tom Peters, Bettina Speckmann, and Frank Staals.

Keywords

  • Bichromatic
  • Classification
  • Duality
  • Geometric Algorithms
  • Separating Line

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