Simple Deterministic Selection-Based Genetic Algorithm for Hyperparameter Tuning of Machine Learning Models

Simple Deterministic Selection-Based Genetic Algorithm for Hyperparameter Tuning of Machine Learning Models

Hyperparameter tuning is a critical function necessary for the effective deployment of most machine learning (ML) algorithms. It is used to find the optimal hyperparameter settings of an ML algorithm in order to improve its overall output performance. To this effect, several optimization strategies...

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Bibliographic Details
Main Authors: Ismail Damilola Raji, Habeeb Bello-Salau, Ime Jarlath Umoh, Adeiza James Onumanyi, Mutiu Adesina Adegboye, Ahmed Tijani Salawudeen
Format: Article
Language:English
Published: MDPI AG 2022-01-01
Series:Applied Sciences
Subjects:
algorithm
convolutional neural network
hyperparameter
random forest
machine learning
metaheuristic
Online Access:https://www.mdpi.com/2076-3417/12/3/1186

Internet

https://www.mdpi.com/2076-3417/12/3/1186

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