Metaheuristics for machine learning : new advances and tools

Metaheuristics for machine learning : new advances and tools / Mansour Eddaly, Bassem Jarboui, Patrick Siarry, editors.

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...

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Bibliographic Details
Other Authors: Eddaly, Mansour (Editor), Jarboui, Bassem (Editor), Siarry, Patrick (Editor)
Format: eBook
Language:English
Published: Singapore : Springer, [2023]
Series:Computational intelligence methods and applications.
Subjects:
Metaheuristics.
Machine learning.
Machine learning
Metaheuristics
Online Access:Click for online access
Table of Contents:
  • 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.

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