Machine Learning for Data Streams : with Practical Examples in MOA /
A hands-on approach to tasks and techniques in data stream mining and real-time analytics, with examples in MOA, a popular freely available open-source software framework.
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| Main Authors: | , , , |
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| 格式: | 電子 電子書 |
| 語言: | 英语 |
| 出版: |
London, England :
The MIT Press,
[2017]
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| 叢編: | Book collections on Project MUSE.
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| 主題: | |
| 在線閱讀: | Full text available: |
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書本目錄:
- Intro; Contents; List of Figures; List of Tables; Preface; I INTRODUCTION; 1 Introduction; 2 Big Data Stream Mining; 3 Hands-on Introduction to MOA; II STREAM MINING; 4 Streams and Sketches; 5 Dealing with Change; 6 Classification; 7 Ensemble Methods; 8 Regression; 9 Clustering; 10 Frequent Pattern Mining; III THE MOA SOFTWARE; 11 Introduction to MOA and Its Ecosystem; 12 The Graphical User Interface; 13 Using the Command Line; 14 Using the API; 15 Developing New Methods in MOA; Bibliography; Index