Rule based systems for big data : a machine learning approach

著者

• Liu, Han
• Gegov, Alexander
• Cocea, Mihaela

書誌事項

Rule based systems for big data : a machine learning approach

Han Liu, Alexander Gegov, Mihaela Cocea

（Studies in big data, v. 13）

Springer, c2016

注記

Includes bibliographical references

内容説明・目次

内容説明

The ideas introduced in this book explore the relationships among rule based systems, machine learning and big data. Rule based systems are seen as a special type of expert systems, which can be built by using expert knowledge or learning from real data. The book focuses on the development and evaluation of rule based systems in terms of accuracy, efficiency and interpretability. In particular, a unified framework for building rule based systems, which consists of the operations of rule generation, rule simplification and rule representation, is presented. Each of these operations is detailed using specific methods or techniques. In addition, this book also presents some ensemble learning frameworks for building ensemble rule based systems.

目次

Introduction.- Theoretical Preliminaries.- Generation of Classification Rules.- Simplification of Classification Rules.- Representation of Classification Rules.- Ensemble Learning Approaches.- Interpretability Analysis.

「Nielsen BookData」 より

詳細情報

• NII書誌ID(NCID): BB20515514
• ISBN:
  • 9783319236957
• 出版国コード: sz
• タイトル言語コード: eng
• 本文言語コード: eng
• 出版地: Cham
• ページ数/冊数: xiii, 121 p.
• 大きさ: 25 cm
• 分類:
  • DC23 : 005.74
  • DC20 : 005.74
• 件名:
  • LCSH : Big data
  • LCSH : Rule-based programming
  • LCSH : Machine learning
• 親書誌ID:
  • BB14129855