{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T11:50:58Z","timestamp":1785757858956,"version":"3.56.0"},"reference-count":37,"publisher":"Wiley","license":[{"start":{"date-parts":[[2022,1,22]],"date-time":"2022-01-22T00:00:00Z","timestamp":1642809600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computational Intelligence and Neuroscience"],"published-print":{"date-parts":[[2022,1,22]]},"abstract":"<jats:p>Customer churn prediction is one of the challenging problems and paramount concerns for telecommunication industries. With the increasing number of mobile operators, users can switch from one mobile operator to another if they are unsatisfied with the service. Marketing literature states that it costs 5\u201310 times more to acquire a new customer than retain an existing one. Hence, effective customer churn management has become a crucial demand for mobile communication operators. Researchers have proposed several classifiers and boosting methods to control customer churn rate, including deep learning (DL) algorithms. However, conventional classification algorithms follow an error-based framework that focuses on improving the classifier\u2019s accuracy over cost sensitization. Typical classification algorithms treat misclassification errors equally, which is not applicable in practice. On the contrary, DL algorithms are computationally expensive as well as time-consuming. In this paper, a novel class-dependent cost-sensitive boosting algorithm called AdaBoostWithCost is proposed to reduce the churn cost. This study demonstrates the empirical evaluation of the proposed AdaBoostWithCost algorithm, which consistently outperforms the discrete AdaBoost algorithm concerning telecom churn prediction. The key focus of the AdaBoostWithCost classifier is to reduce false-negative error and the misclassification cost more significantly than the AdaBoost.<\/jats:p>","DOI":"10.1155\/2022\/9028580","type":"journal-article","created":{"date-parts":[[2022,1,22]],"date-time":"2022-01-22T18:05:12Z","timestamp":1642874712000},"page":"1-11","source":"Crossref","is-referenced-by-count":24,"title":["Clairvoyant: AdaBoost with Cost-Enabled Cost-Sensitive Classifier for Customer Churn Prediction"],"prefix":"10.1155","volume":"2022","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4196-7651","authenticated-orcid":true,"given":"Hiren Kumar","family":"Thakkar","sequence":"first","affiliation":[{"name":"Department of Computer Engineering, Marwadi University, 360003 Rajkot, Gujarat, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3109-9608","authenticated-orcid":true,"given":"Ankit","family":"Desai","sequence":"additional","affiliation":[{"name":"Ahmedabad University, Ahmedabad, Gujarat, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Subrata","family":"Ghosh","sequence":"additional","affiliation":[{"name":"Ambient Scientific, Bangalore, Karnataka, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Priyanka","family":"Singh","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, School of Engineering and Sciences, SRM University, Amaravati 522240, Andhra Pradesh, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5695-8611","authenticated-orcid":true,"given":"Gajendra","family":"Sharma","sequence":"additional","affiliation":[{"name":"School of Engineering, Department of Computer Science and Engineering, Kathmandu University, Dhulikhel, Kavre 45200, Nepal"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","reference":[{"issue":"1","key":"1","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1109\/MCE.2016.2614420","article-title":"CE-driven trends in global communications: strategic sectors for economic growth and development","volume":"6","author":"S. 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