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Machine Learning Paradigms: Theory and Application
The book focuses on machine learning. Divided into three parts, the first part discusses the feature selection problem. The second part then describes the application of machine learning in the classification problem, while the third part presents an overview of real-world applications of swarm-base...
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| Format: | e-Book |
| Language: | English |
| Published: |
Cham :
Springer International Publishing : Imprint: Springer,
2019.
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| Edition: | 1st ed. 2019. |
| Series: | Studies in Computational Intelligence,
801 |
| Subjects: | |
| Online Access: | Full-text access View in OPAC |
Table of Contents:
- Part I: Machine Learning in Feature Selection
- Hybrid Feature Selection Method Based On The Genetic Algorithm And Pearson Correlation Coefficient
- Weighting Attributes and Decision Rules through Rankings and Discretisation Parameters
- Greedy Selection of Attributes to be Discretised
- Part II: Machine Learning in Classification and Ontology
- Machine learning for Enhancement Land Cover and Crop Types Classification.