Data Mining Concepts and Techniques

Livro digital

Título:
Data Mining Concepts and Techniques

Autor:
Jiawei Han, Micheline Kamber, Jian Pei

Categoria:
Tecnologia > Dados

Doador:
Raffaello D. N.

Sinopse:
Readers who want a practical map of the field will find it here, starting from the book’s own progression: Chapter 1 opens with why data mining matters, what can be mined, and which patterns are interesting, then moves into the core workflow of data preprocessing and data understanding. The table of contents shows a broad and carefully layered structure, from attribute types, statistics, similarity measures, and visualization to cleaning, integration, reduction, transformation, and discretization. It then expands into data warehousing, OLAP, data cube computation, multidimensional models, and attribute-oriented induction, before moving on to classification, clustering, association analysis, and advanced topics like mining complex data types. The result is a comprehensive reference for readers who need both conceptual grounding and implementation-minded detail. Its value lies in connecting foundational data management ideas to modern mining techniques, making it useful for students, practitioners, and anyone building a serious understanding of data mining systems.