---
title: An Automated Hyperparameter Tuning Approach For Optimizing Machine Learning Model Performance
url: https://www.ml-quant.com/papers/ssrn/5234657/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: SSRN 5234657
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5234657
featured: 2025-04-30
citations: 0
topic: ML & AI Methods
---


# An Automated Hyperparameter Tuning Approach For Optimizing Machine Learning Model Performance

The study suggests a new automated method for fine-tuning machine learning models using optimization techniques like Bayesian Optimization, Genetic Algorithms, and Reinforcement Learning.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5234657
- Identifier: SSRN 5234657
- Released: 2019-06-05
- First featured: Quant Letter No. 95 (2025-04-30): https://www.ml-quant.com/issues/2025-04-30/
- Citations (Semantic Scholar): 0
- Published in: not yet
- Topic: ML & AI Methods

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