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商品詳細
Hands-on Pattern Mining: Theory and Examples with PAMI, Sklearn, Keras, and TensorFlow.
・ISBN 978-981-9667-93-2 paper EUR 59.99
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| 著者・編者 | Rage, Uday Kiran, |
|---|---|
| 出版社 | (Springer Nature Switzerland AG, SZ) |
| 出版年月 | 2026 |
| ページ数 | 182 pp. |
| 言語 | ENG |
| ニュース番号 | ＜A05-93482＞ |
解説
This book introduces pattern mining by presenting various pattern mining techniques and giving hands-on experience with each technique. Pattern mining is a popular data mining technique with many real-world applications, and involves discovering all user interest-based patterns that may exist in a database. Several models and numerous algorithms were described in the literature to find these patterns in binary databases, quantitative databases, uncertain databases, and streams. Since the lack of a Python toolkit containing these algorithms has limited the wide adaptability of pattern-mining techniques, the author developed Pattern Mining (PAMI) Python library, which currently contains 80+ algorithms to discover useful patterns in transactional databases, temporal databases, quantitative databases, and graphs.
The book consists of three main parts:
? Introduction: The first chapter introduces big data, types of learning techniques, and the importance of pattern mining. The second chapter introduces the PAMI library, its organizational structure, installation, and usage.
? Pattern mining algorithms and examples: The following chapters present the state-of-the-art techniques for discovering user interest-based patterns in (1) transactional databases, (2) temporal databases, (3) quantitative databases, (4) uncertain databases, (5) sequential databases, and (6) graphs.
? Applications: The book concludes with several applications, where the predicted knowledge using TensorFlow and PyTorch was transformed into a database to discover future trends or patterns.