Empirical approach to machine learning. (2018)
- Record Type:
- Book
- Title:
- Empirical approach to machine learning. (2018)
- Main Title:
- Empirical approach to machine learning
- Further Information:
- Note: Plamen P. Angelov, Xiaowei Gu.
- Authors:
- Angelov, Plamen P
Gu, Xiaowei - Contents:
- Introduction.- Part I: Theoretical Background.- Brief Introduction to Statistical Machine Learning.- Brief Introduction to Computational Intelligence.- Part II: Theoretical Fundamentals of the Proposed Approach.- Empirical Approach - Introduction.- Empirical Fuzzy Sets and Systems.- Anomaly Detection - Empirical Approach.- Data Partitioning - Empirical Approach.- Autonomous Learning Multi-Model Systems.- Transparent Deep Rule-Based Classifiers.- Part III: Applications of the Proposed Approach.- Applications of Autonomous Anomaly Detection.
- Publisher Details:
- Cham : Springer
- Publication Date:
- 2018
- Copyright Date:
- 2019
- Extent:
- 1 online resource (423 pages)
- Subjects:
- 006.31
Machine learning
Machine learning - Languages:
- English
- ISBNs:
- 9783030023843
- Related ISBNs:
- 9783030023836
- Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
- Access Usage:
- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.341638
- Ingest File:
- 02_336.xml