An Optimization Approach for Optimizing PRIM’s Randomly Generated Rules Using the Genetic Algorithm

Author:

Nassih Rym,Berrado Abdelaziz

Publisher

Springer Nature Switzerland

Reference17 articles.

1. Goldberg, D.E.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Longman Publishing Co., Inc., Boston (1989)

2. Nassih, R., Berrado, A.: Potential for PRIM based classification: a literature review. In: The Third European International Conference on Industrial Engineering and Operations Managements in Pilsen, Czech Republic, p. 7 (2019)

3. Friedman, J.H., Fisher, N.I.: Bump hunting in high-dimensional data. Stat. Comput. 9(2), 123–143 (1999)

4. Sastry, K., Goldberg, D., Kendall, G.: Genetic algorithms. In: Burke, E.K., Kendall, G. (eds.) Search Methodologies, pp. 97–125. Springer, Boston, MA (2005). https://doi.org/10.1007/0-387-28356-0_4

5. Ruder, S.: An overview of gradient descent optimization algorithms. arXiv preprint arXiv:1609.04747 (2016)

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