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The existing fairness definitions in clustering scenarios mostly deal with Balance of the clusters or the representation of sensitive groups in the clusters. We developed a new algorithm called Fair Maximum Margin Clustering (FMMC), by incorporating the disparate impact criteria into the Maximum Margin Clustering (MMC) algorithm. The FMMC algorithm ensures that the distance of each data point from hyperplane is uncorrelated with that data point\u2019s sensitive attribute value. This constraint is designed to prevent any sensitive group from being negatively impacted by the decision boundary. We show that the performance of the FMMC algorithm is better than that of MMC algorithm in terms of traditional fairness measures such as Balance. We also demonstrate that the FMMC algorithm achieves fair clustering while maintaining the clustering performance of the original MMC algorithm. We validate the effectiveness of our approach through experiments on synthetic and real-world datasets.<\/jats:p>","DOI":"10.1145\/3770078","type":"journal-article","created":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T13:43:21Z","timestamp":1759326201000},"page":"1-24","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Towards Fair Decision Boundaries in Clustering: Integrating Disparate Impact Criteria into Maximum Margin Clustering"],"prefix":"10.1145","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-2871-8548","authenticated-orcid":false,"given":"Adithya K.","family":"Moorthy","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, Indian Institute of Technology Guwahati, Guwahati, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-5003-3716","authenticated-orcid":false,"given":"Jaya Teja Reddy","family":"Pochimireddy","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Indian Institute of Technology Guwahati, Guwahati, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7856-5322","authenticated-orcid":false,"given":"Vijaya Saradhi","family":"Vedula","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Indian Institute of Technology Guwahati, Guwahati, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3585-655X","authenticated-orcid":false,"given":"Bhanu","family":"Prasad","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Sciences, Florida Agricultural and Mechanical University, Tallahassee, Florida, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,11,6]]},"reference":[{"key":"e_1_3_1_2_2","unstructured":"[n. d.]. 2024. 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