A Systematic Assessment of Genetic Algorithm (GA) in Optimizing Machine Learning Model: A Case Study from Building Science
Author:
Affiliation:
1. Khalifa University,Department of Engineering Systems and Management,Abu Dhabi,United Arab Emirates
2. Carleton University,Department of Civil and Environmental Engineering,Ottawa,ON,Canada
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9989527/9989519/09989719.pdf?arnumber=9989719
Reference29 articles.
1. Efficient Hyperparameter Optimization in Deep Learning Using a Variable Length Genetic Algorithm;xiao;arXiv preprint arXiv 2006 12703,2020
2. Large-scale evolution of image classifiers;real;arXiv preprint arXiv 1703 01281,2017
3. Model selection of SVMs using GA approach
4. Tuning the Structure and Parameters of a Neural Network by Using Hybrid Taguchi-Genetic Algorithm
5. Optimizing deep learning hyper-parameters through an evolutionary algorithm. In: MLHPC’15 Proceedings of the Workshop on Machine Learning in High-Performance Computing Environments, Article No. 4;young;Oak Ridge National Laboratory Oak Ridge Leadership Computing Facility (OLCF) Tech Rep,2015
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