Evaluation of Performance of Feature Selection of Meta-Heuristic Optimization Methods in Medical Data

Year 2023, Volume: IDAP-2023 : International Artificial Intelligence and Data Processing Symposium Issue: IDAP-2023, 58 - 66, 18.10.2023

Hüseyin Gündoğdu , Osman Altay

https://doi.org/10.53070/bbd.1351629

Abstract

In knowledge discovery, the processes of applying data cleaning, data integration, data selection-transformation, and data mining methods and obtaining meaningful information from the obtained patterns are performed, respectively. In recent years, it has become quite common to use metaheuristic optimization methods in the data selection phase. In this study, the nearest neighbor algorithm, support vector machine, and decision tree algorithms from machine learning algorithms were used on health data obtained from the University of California, Irvine. The whale optimization algorithm, salp swarm optimization, slime mould optimization, particle swarm optimization, and Harris Hawks optimization methods were used for feature selection. The obtained results were compared in detail.

Keywords

Feature selection, meta-heuristic optimization algorithms, Whale optimization algorithm, Harris Hawks optimization

Tıp Verilerinde Meta-Sezgisel Optimizasyon Yöntemlerinin Özellik Seçimi Performanslarının Karşılaştırılması

Abstract

Bilgi keşfinde sırasıyla veri temizleme, veri bütünleştirme, veri seçme-dönüştürme ve veri madenciliği yöntemlerini uygulama ve elde edilen örüntülerden anlamlı bilgiler elde etme süreçleri gerçekleştirilir. Son yıllarda veri seçimi aşamasında metasezgisel optimizasyon yöntemlerinin kullanılması oldukça yaygın hale gelmiştir. Bu çalışmada California Üniversitesi, Irvine'den elde edilen sağlık verileri üzerinde makine öğrenmesi algoritmalarından en yakın komşu algoritması, destek vektör makinesi ve karar ağacı algoritmaları kullanılmıştır. Özellik seçimi için balina optimizasyon algoritması, salp sürü optimizasyonu, slime küf optimizasyonu, parçacık sürü optimizasyonu ve Harris Hawks optimizasyon yöntemleri kullanılmıştır. Elde edilen sonuçlar ayrıntılı olarak karşılaştırılmıştır.

Keywords

Özellik Seçimi, Meta-Sezgisel Optimizasyon Algoritmaları, Baline Optimizasyonu, Harris Şahini Optimizasyonu

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