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Found 3 papers, 1 papers with code
OptABC: an Optimal Hyperparameter Tuning Approach for Machine Learning Algorithms
OptABC integrates artificial bee colony algorithm, K-Means clustering, greedy algorithm, and opposition-based learning strategy for tuning the hyper-parameters of different machine learning models.
HyP-ABC: A Novel Automated Hyper-Parameter Tuning Algorithm Using Evolutionary Optimization
In order to ensure the robustness of the proposed method, the algorithm takes a wide range of feasible hyper-parameter values, and is tested using a real-world educational dataset.
Search Algorithms for Automated Hyper-Parameter Tuning
In this paper, we examine the effectiveness of automated hyper-parameter tuning techniques to the realm of students' success.
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