Foundations and methods in combinatorial and statistical data analysis and clustering
- 作者： Lerman, Israel Cesar, author.
- 其他作者：
- 其他題名：
- Advanced information and knowledge processing.
- 出版： London : Springer London :Imprint: Springer
- 叢書名： Advanced information and knowledge processing,
- 主題： Combinatorial analysis. , Document clustering. , Quantitative research. , Computer Science. , Data Mining and Knowledge Discovery. , Statistics and Computing/Statistics Programs. , Combinatorics.
- ISBN： 9781447167938 (electronic bk.) 、 9781447167914 (paper)
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FIND@SFXID:
CGU
- 資料類型: 電子書
- 內容註: Preface -- On Some Facets of the Partition Set of a Finite Set -- Two Methods of Non-hierarchical Clustering -- Structure and Mathematical Representation of Data -- Ordinal and Metrical Analysis of the Resemblance Notion -- Comparing Attributes by a Probabilistic and Statistical Association I -- Comparing Attributes by a Probabilistic and Statistical Association II -- Comparing Objects or Categories Described by Attributes -- The Notion of "Natural" Class, Tools for its Interpretation. The Classifiability Concept -- Quality Measures in Clustering -- Building a Classification Tree -- Applying the LLA Method to Real Data -- Conclusion and Thoughts for Future Works.
- 摘要註: This book offers an original and broad exploration of the fundamental methods in Clustering and Combinatorial Data Analysis, presenting new formulations and ideas within this very active field. With extensive introductions, formal and mathematical developments and real case studies, this book provides readers with a deeper understanding of the mutual relationships between these methods, which are clearly expressed with respect to three facets: logical, combinatorial and statistical. Using relational mathematical representation, all types of data structures can be handled in precise and unified ways which the author highlights in three stages: Clustering a set of descriptive attributes Clustering a set of objects or a set of object categories Establishing correspondence between these two dual clusterings Tools for interpreting the reasons of a given cluster or clustering are also included. Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering will be a valuable resource for students and researchers who are interested in the areas of Data Analysis, Clustering, Data Mining and Knowledge Discovery.
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讀者標籤：
- 系統號： 005359898 | 機讀編目格式
館藏資訊
This book offers an original and broad exploration of the fundamental methods in Clustering and Combinatorial Data Analysis, presenting new formulations and ideas within this very active field. With extensive introductions, formal and mathematical developments and real case studies, this book provides readers with a deeper understanding of the mutual relationships between these methods, which are clearly expressed with respect to three facets: logical, combinatorial and statistical. Using relational mathematical representation, all types of data structures can be handled in precise and unified ways which the author highlights in three stages: Clustering a set of descriptive attributes Clustering a set of objects or a set of object categories Establishing correspondence between these two dual clusterings Tools for interpreting the reasons of a given cluster or clustering are also included. Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering will be a valuable resource for students and researchers who are interested in the areas of Data Analysis, Clustering, Data Mining and Knowledge Discovery.