Developing Churn Models Using Data Mining Techniques and Social Network Analysis - Robert Kopal,Leo Mr¿i¿,Goran Klepac
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Piegāde 17-23 darba dienu laikā
30 dienu atgriešanas politika
Churn prediction, recognition, and mitigation have become essential topics in various industries. As a means for forecasting and managing risk, further research in this field can greatly assist companies in making informed decisions based on future possible scenarios. Developing Churn Models Using Data Mining Techniques and Social Network Analysis provides an in-depth analysis of attrition modeling relevant ... Pilns apraksts
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Aprašymas
Churn prediction, recognition, and mitigation have become essential topics in various industries. As a means for forecasting and managing risk, further research in this field can greatly assist companies in making informed decisions based on future possible scenarios. Developing Churn Models Using Data Mining Techniques and Social Network Analysis provides an in-depth analysis of attrition modeling relevant to business planning and management. Through its insightful and detailed explanation of best practices, tools, and theory surrounding churn prediction and the integration of analytics tools, this publication is especially relevant to managers, data specialists, business analysts, academicians, and upper-level students.
Vairāk informācijas
| Autors | Robert Kopal, Leo Mr¿i¿, Goran Klepac |
|---|---|
| Izdevējs | Information Science Reference |
| Izlaides gads | 2014 |
| Vāka tips | Cietais vāks |
| EAN | 9781466662889 |