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SUPERVISED DESCRIPTIVE PATTERN MINING IBD

SPRINGER
10 / 2018
9783319981390
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Sinopse

This book provides a general and comprehensible overview ofásupervised descriptive pattern mining, considering classicáalgorithms and those based on heuristics. áIt providesásome formal definitions and a general idea about patterns, pattern mining,áthe usefulness of patterns in the knowledge discovery process, as well as aábrief summary on the tasks related to supervised descriptive patternámining. It also includes a detailed description on the tasks usually groupedáunder the term supervised descriptive pattern mining: subgroups discovery,ácontrast sets and emerging patterns. Additionally, this book includes twoátasks, class association rules and exceptional models, that are alsoáconsidered within this field.A major feature of this book is that it provides a general overview (formaládefinitions and algorithms) of all the tasks included under the termásupervised descriptive pattern mining.áIt considers the analysis of different algorithms either based on heuristics or based on exhaustive search methodologies foráany of these tasks. This book also illustrates how important these techniques areáin different fields, a set of real-world applications are described.Last but not least, some related tasks are also considered and analyzed.áThe final aim of this book is to provide a general review of the supervisedádescriptive pattern mining field, describing its tasks, its algorithms, its applications,áand related tasks (those that share some common features).This book átargets developers, engineers and computer scientists aiming to apply classic and heuristic-basedáalgorithms to solve different kinds of pattern mining problems and apply them to real issues.áStudents and researchers working in this field, can use this comprehensive book (which includes its methodsáand tools) as a secondary textbook.

PVP
133,00