Data Mining With Decision Trees: Theory And Applications (2nd Edition)

Автор: Lior Rokach, Oded Z. Maimon

Език:

Корици: С твърди корици

Издател: World Scientific Publishing Co Pte Ltd

Наличност: Външен склад

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120.13 € 234.95 лв

Decision trees have become one of the most powerful and popular approaches in knowledge discovery an...

Информация за книгата

Автор

Lior Rokach, Oded Z. Maimon

Език

Английски език

Корици

Книга - С твърди корици

Издадена

2014

страници

328

EAN

9789814590075

ISBN

981459007X

Enbook ID

05071275

Издател

World Scientific Publishing Co Pte Ltd

Теглоt

602

Размери

234 x 160 x 25

Пълно описание

Decision trees have become one of the most powerful and popular approaches in knowledge discovery and data mining; it is the science of exploring large and complex bodies of data in order to discover useful patterns. Decision tree learning continues to evolve over time. Existing methods are constantly being improved and new methods introduced. This 2nd Edition is dedicated entirely to the field of decision trees in data mining; to cover all aspects of this important technique, as well as improved or new methods and techniques developed after the publication of our first edition. In this new edition, all chapters have been revised and new topics brought in. New topics include Cost-Sensitive Active Learning, Learning with Uncertain and Imbalanced Data, Using Decision Trees beyond Classification Tasks, Privacy Preserving Decision Tree Learning, Lessons Learned from Comparative Studies, and Learning Decision Trees for Big Data. A walk-through guide to existing open-source data mining software is also included in this edition. This book invites readers to explore the many benefits in data mining that decision trees offer: Self-explanatory and easy to follow when compacted Able to handle a variety of input data: nominal, numeric and textual Scales well to big data Able to process datasets that may have errors or missing values High predictive performance for a relatively small computational effort Available in many open source data mining packages over a variety of platforms Useful for various tasks, such as classification, regression, clustering and feature selection

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Data Mining With Decision Trees: Theory And Applications (2nd Edition)

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