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Supervised descriptive pattern mining

Luna, Jose Maria.

Supervised descriptive pattern mining

Record Type:	Electronic resources : Monograph/item
Title/Author:	Supervised descriptive pattern miningby Sebastian Ventura, Jose Maria Luna.
Author:	Ventura, Sebastian.
other author:	Luna, Jose Maria.
Published:	Cham :Springer International Publishing :2018.
Description:	xi, 185 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Data mining.
Online resource:	https://doi.org/10.1007/978-3-319-98140-6
ISBN:	9783319981406$q(electronic bk.)

Supervised descriptive pattern mining
Ventura, Sebastian.

Supervised descriptive pattern mining[electronic resource] /by Sebastian Ventura, Jose Maria Luna. - Cham :Springer International Publishing :2018. - xi, 185 p. :ill., digital ;24 cm.

1 Introduction to Supervised Descriptive Pattern Mining -- 2 Contrast Sets -- 3 Emerging Patterns -- 4 Subgroup Discovery -- 5 Class Association Rules -- 6 Exceptional Models -- 7 Other Forms of Supervised Descriptive Pattern Mining -- 8 Successful Applications.

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

ISBN: 9783319981406$q(electronic bk.)

Standard No.: 10.1007/978-3-319-98140-6doiSubjects--Topical Terms:

184440
Data mining.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 006.312

Supervised descriptive pattern mining
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100 1 $a Ventura, Sebastian. $3 749711
245 1 0 $a Supervised descriptive pattern mining $h [electronic resource] / $c by Sebastian Ventura, Jose Maria Luna.
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300 $a xi, 185 p. : $b ill., digital ; $c 24 cm.
505 0 $a 1 Introduction to Supervised Descriptive Pattern Mining -- 2 Contrast Sets -- 3 Emerging Patterns -- 4 Subgroup Discovery -- 5 Class Association Rules -- 6 Exceptional Models -- 7 Other Forms of Supervised Descriptive Pattern Mining -- 8 Successful Applications.
520 $a This book provides a general and comprehensible overview of supervised descriptive pattern mining, considering classic algorithms and those based on heuristics. It provides some formal definitions and a general idea about patterns, pattern mining, the usefulness of patterns in the knowledge discovery process, as well as a brief summary on the tasks related to supervised descriptive pattern mining. It also includes a detailed description on the tasks usually grouped under the term supervised descriptive pattern mining: subgroups discovery, contrast sets and emerging patterns. Additionally, this book includes two tasks, class association rules and exceptional models, that are also considered within this field. A major feature of this book is that it provides a general overview (formal definitions and algorithms) of all the tasks included under the term supervised descriptive pattern mining. It considers the analysis of different algorithms either based on heuristics or based on exhaustive search methodologies for any of these tasks. This book also illustrates how important these techniques are in different fields, a set of real-world applications are described. Last but not least, some related tasks are also considered and analyzed. The final aim of this book is to provide a general review of the supervised descriptive pattern mining field, describing its tasks, its algorithms, its applications, and related tasks (those that share some common features) This book targets developers, engineers and computer scientists aiming to apply classic and heuristic-based algorithms to solve different kinds of pattern mining problems and apply them to real issues. Students and researchers working in this field, can use this comprehensive book (which includes its methods and tools) as a secondary textbook.
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650 2 4 $a Pattern Recognition. $3 273706
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