| 书目名称 | Inductive Fuzzy Classification in Marketing Analytics |
| 编辑 | Michael Kaufmann |
| 视频video | |
| 概述 | Provides a solid foundation of fuzzy classification and inductive logic and their application in marketing.Includes a case study of a real world application at a financial institute.Visualizes the abs |
| 丛书名称 | Fuzzy Management Methods |
| 图书封面 |  |
| 描述 | To enhance marketing analytics, approximate and inductive reasoning can be applied to handle uncertainty in individual marketing models. This book demonstrates the use of fuzzy logic for classification and segmentation in marketing campaigns. Based on practical experience as a data analyst and on theoretical studies as a researcher, the author explains fuzzy classification, inductive logic and the concept of likelihood and introduces a blend of Bayesian and Fuzzy Set approaches, allowing reasonings on fuzzy sets that are derived by inductive logic. By application of this theory, the book guides the reader towards a gradual segmentation of customers which can enhance return on targeted marketing campaigns. The algorithms presented can be used for visualization, selection and prediction. The book shows how fuzzy logic can complement customer analytics by introducing fuzzy target groups. This book is for researchers, analytics professionals, data miners and students interested in fuzzy classification for marketing analytics. |
| 出版日期 | Book 2014 |
| 关键词 | Data mining; Fuzzy classification; Fuzzy set; Inductive logic; Marketing analytics; Segmentation |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-05861-0 |
| isbn_softcover | 978-3-319-38160-2 |
| isbn_ebook | 978-3-319-05861-0Series ISSN 2196-4130 Series E-ISSN 2196-4149 |
| issn_series | 2196-4130 |
| copyright | Springer International Publishing Switzerland 2014 |
发表于 2025-3-21 17:19:28
