Developing Churn Models Using Data Mining Techniques and Social Network Analysis - Goran Klepac, Robert Kopal, Leo Mr�i

Developing Churn Models Using Data Mining Techniques and Social Network Analysis

Buch | Hardcover
361 Seiten
2014
Idea Group,U.S. (Verlag)
978-1-4666-6288-9 (ISBN)
229,45 inkl. MwSt
Churn prediction, recognition, and mitigation have become essential topics in various industries. As a means for forecasting and manageing risk, further research in this field can greatly assist companies in making informed decisions based on future possible scenarios. This title provides an in-depth analysis of attrition modelling relevant to business planning and management.
Churn prediction, recognition, and mitigation have become essential topics in various industries. As a means for forecasting and manageing 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.

Goran Klepac, Raiffeisenbank Austria Zagreb, Croatia. Robert Kopal University College for Law and Finance Effectus Zagreb, Croatia and University College for Applied Computer Engineering Algebra Zagreb, Croatia. Leo Mršić University College for Law and Finance Effectus Zagreb, Croatia and University College for Applied Computer Engineering Algebra Zagreb, Croatia.

Reihe/Serie Research Essentials Collection
Verlagsort Harrisburg, PA
Sprache englisch
Maße 152 x 229 mm
Gewicht 765 g
Themenwelt Informatik Datenbanken Data Warehouse / Data Mining
ISBN-10 1-4666-6288-3 / 1466662883
ISBN-13 978-1-4666-6288-9 / 9781466662889
Zustand Neuware
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