Advances in nature-inspired metaheuristic optimization for feature selection problem: A comprehensive survey

M Nssibi, G Manita, O Korbaa - Computer Science Review, 2023 - Elsevier
The main objective of feature selection is to improve learning performance by selecting
concise and informative feature subsets, which presents a challenging task for machine …

A study on credit scoring modeling with different feature selection and machine learning approaches

SK Trivedi - Technology in Society, 2020 - Elsevier
A bit hurdle for financial institutions is to decide potential candidates to give a line of credit
identifying the right people without any credit risk. For such a crucial decision, past …

A high-dimensionality-trait-driven learning paradigm for high dimensional credit classification

L Yu, L Yu, K Yu - Financial Innovation, 2021 - Springer
To solve the high-dimensionality issue and improve its accuracy in credit risk assessment, a
high-dimensionality-trait-driven learning paradigm is proposed for feature extraction and …

Feature selection based on machine learning for credit scoring: An evaluation of filter and embedded methods

A Siham, S Sara, A Abdellah - 2021 International conference on …, 2021 - ieeexplore.ieee.org
Feature Selection (FS) is one of the power solutions used in Machine Learning (ML)
problems, since it can help to remove irrelevant and redundant attributes, improve the …

Initialization of feature selection search for classification

M Luque-Rodriguez, J Molina-Baena… - Journal of Artificial …, 2022 - jair.org
Selecting the best features in a dataset improves accuracy and efficiency of classifiers in a
learning process. Datasets generally have more features than necessary, some of them …

An Opposition-Based Great Wall Construction Metaheuristic Algorithm With Gaussian Mutation for Feature Selection

F Zitouni, AS Almazyad, G Xiong, AW Mohamed… - IEEE …, 2024 - ieeexplore.ieee.org
The feature selection problem involves selecting a subset of relevant features to enhance
the performance of machine learning models, crucial for achieving model accuracy. Its …

Combined feature selection and rule extraction for credit applicant classification

S Akil, S Sekkate, A Adib - … Proceedings of the International Conference on …, 2022 - Springer
A sensitive area such as credit risk assessment has always been a high priority and quite
difficult for financial institutions to make financial decisions. In order to have a more relevant …

A Review Study of AI Methods for Credit Default Prediction

MA Mandour, G Chi - International Conference on Deep Learning and …, 2024 - Springer
Research using empirical and analytical approaches from the field of artificial intelligence
(AI) has found credit default to be a fascinating issue. The article shows a systematic …

[PDF][PDF] Feature Selection Using Quantum Inspired Island Model Genetic Algorithm for Wheat Rust Disease Detection and Severity Estimation

S Samanta, S Chatterji, S Pratihar - Proceedings Copyright, 2024 - scitepress.org
In the context of smart agriculture, an early disease detection system is crucial to increase
agricultural yield. A disease detection system based on machine learning can be an …

An Opposition-Based Great Wall Construction Metaheuristic Algorithm with Gaussian Mutation for Feature Selection

A Bassimane, M Hammadi - dspace.univ-ouargla.dz
The feature selection problem involves selecting a subset of relevant features to en-hance
the performance of machine learning models, crucial for achieving model accuracy. Its …