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The genuine and malicious samples are removed and only the suspicious instances are further scrutinized in the second stage by four trained supervised classifiers \u2212 Decision Tree, Support Vector Machine, Group Method for Data Handling and Multi-Layer Perceptron individually for final decision making. Extensive experiments and comparative analysis with another recent approach using a real-world automobile insurance dataset justifies the effectiveness of the proposed system.<\/jats:p>","DOI":"10.4018\/ijisp.2020070102","type":"journal-article","created":{"date-parts":[[2020,6,2]],"date-time":"2020-06-02T09:38:36Z","timestamp":1591090716000},"page":"18-37","source":"Crossref","is-referenced-by-count":7,"title":["Two-Stage Automobile Insurance Fraud Detection by Using Optimized Fuzzy C-Means Clustering and Supervised Learning"],"prefix":"10.4018","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5043-1533","authenticated-orcid":true,"given":"Sharmila","family":"Subudhi","sequence":"first","affiliation":[{"name":"ITER, Siksha 'O' Anusandhan Deemed to be University, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Suvasini","family":"Panigrahi","sequence":"additional","affiliation":[{"name":"Veer Surendra Sai University of Technology, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"IJISP.2020070102-0","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2016.04.007"},{"key":"IJISP.2020070102-1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejor.2013.06.023"},{"key":"IJISP.2020070102-2","doi-asserted-by":"publisher","DOI":"10.1016\/0098-3004(84)90020-7"},{"key":"IJISP.2020070102-3","first-page":"589","article-title":"Optimization of fuzzy clustering criteria using genetic algorithms.","author":"J. 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