Metaheuristics for Machine Learning New Advances and Tools /
Using metaheuristics to enhance machine learning techniques has become trendy and has achieved major successes in both supervised (classification and regression) and unsupervised (clustering and rule mining) problems. Furthermore, automatically generating programs via metaheuristics, as a form of ev...
Shranjeno v:
| Korporativna značnica: | |
|---|---|
| Drugi avtorji: | , , |
| Format: | Elektronski eKnjiga |
| Jezik: | angleščina |
| Izdano: |
Singapore :
Springer Nature Singapore : Imprint: Springer,
2023.
|
| Izdaja: | 1st ed. 2023. |
| Serija: | Computational Intelligence Methods and Applications,
|
| Teme: | |
| Online dostop: | https://doi.org/10.1007/978-981-19-3888-7 |
| Oznake: |
Označite
Brez oznak, prvi označite!
|
Kazalo:
- 1. From metaheuristics to automatic programming
- 2. Biclustering Algorithms Based on Metaheuristics: A Review
- 3. A Metaheuristic Perspective on Learning Classifier Systems
- 4. An evolutionary clustering approach using metaheuristics and unsupervised machine learning algorithms for customer segmentation
- 5. Applications of Metaheuristics in Parameter Optimization in Manufacturing Processes and Machine Health Monitoring
- 6. Evolving Machine Learning-based classifiers by metaheuristic approaches for underwater sonar target detection and recognition
- 7. Solving the Quadratic Knapsack Problem using a GRASP algorithm based on a multi-swap local search
- 8. Algorithmic vs Processing Manipulations to Scale Genetic Programming to Big Data Mining
- 9. Dynamic assignment problem of parking slots.