Nature-Inspired Computation in Data Mining and Machine Learning
| 団体著者: | |
|---|---|
| その他の著者: | , |
| 要約: | XI, 273 p. 87 illus., 66 illus. in color. text |
| 言語: | 英語 |
| 出版事項: |
Cham :
Springer International Publishing : Imprint: Springer,
2020.
|
| 版: | 1st ed. 2020. |
| シリーズ: | Studies in Computational Intelligence,
855 |
| 主題: | |
| オンライン･アクセス: | https://doi.org/10.1007/978-3-030-28553-1 |
| フォーマット: | 電子媒体 eBook |
目次:
- Adaptive Improved Flower Pollination Algorithm for Global Optimization
- Algorithms for Optimization and Machine Learning over Cloud
- Implementation of Machine Learning and Data Mining to Improve Cybersecurity and Limit Vulnerabilities to Cyber Attacks
- Comparative analysis of different classifiers on crisis-related tweets: An elaborate study
- An Improved Extreme Learning Machine Tuning by Flower Pollination Algorithm
- Prospects of Machine and Deep Learning in Analysis of Vital Signs for the Improvement of Healthcare Services.