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While the second case study presents a more traditional example, where the aim is to predict organizations likely to cease being a subscriber to a service. The case studies include presentation of the accuracy of the models using a standard methodology as well as comparing the results with what happened in practice. Both case studies show the significant savings that can be made, plus potential increase in revenue by using decision tree learning for churn analysis.<\/jats:p>","DOI":"10.4018\/ijcssa.2017070102","type":"journal-article","created":{"date-parts":[[2017,9,13]],"date-time":"2017-09-13T01:09:23Z","timestamp":1505264963000},"page":"22-33","source":"Crossref","is-referenced-by-count":1,"title":["Case Studies in Applying Data Mining for Churn Analysis"],"prefix":"10.4018","volume":"5","author":[{"given":"Susan","family":"Lomax","sequence":"first","affiliation":[{"name":"University of Salford, Salford, UK"}]},{"given":"Sunil","family":"Vadera","sequence":"additional","affiliation":[{"name":"University of Salford, Salford, UK"}]}],"member":"2432","reference":[{"key":"IJCSSA.2017070102-0","doi-asserted-by":"publisher","DOI":"10.1142\/S0219622008003137"},{"key":"IJCSSA.2017070102-1","doi-asserted-by":"publisher","DOI":"10.1287\/mksc.17.1.45"},{"key":"IJCSSA.2017070102-2","unstructured":"Deshpande, B. 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