Determining critical factors for the success of machine learning libraries considering fuzzy interrelationships

Öz

Advances in Machine Learning have led to groundbreaking developments across various fields. A key driver of this progress is the growing capabilities of machine learning libraries. However, these libraries still face certain limitations, which can hinder their application in some areas. In particular, developers often need to integrate their solutions across different libraries, languages, and platforms, which can reduce the effectiveness of machine learning applications. This study examines the direct and indirect impacts of various factors on the success of machine learning libraries, leveraging expert evaluations. Focusing on critical factors that shape library development based on user experiences is crucial. This approach ensures strategic advancement and optimizes energy and resource use. Given that many of these factors involve human perception-related uncertainties, the methodology incorporates a fuzzy linguistic approach with z-numbers to address the inherent vagueness. The findings reveal that considering the interrelationships among factors significantly alters their importance, as it accounts for both direct and indirect influences. Moreover, these interrelationships highlight which factors should be strategically prioritized, as improvements in one factor can drive improvements in others. The results obtained can support guiding the community developing artificial intelligence libraries toward the right objectives and formulating effective strategies to ensure the sustainability of artificial intelligence transformation. 

Anahtar Kelimeler

• Artificial intelligence
• Fuzzy logic
• Linguistic term set
• Machine learning libraries
• Z-number

Makine öğrenmesi kütüphanelerinin başarısı için kritik faktörlerin bulanık karşılıklı ilişkiler göz önünde bulundurularak belirlenmesi

Öz

Makine öğrenmesindeki ilerlemeler, çeşitli alanlarda çığır açan gelişmelere yol açmıştır. Bu ilerlemenin temel itici güçlerinden biri, makine öğrenmesi kütüphanelerinin artan yetenekleridir. Ancak, bu kütüphaneler hâlâ bazı sınırlamalara sahiptir ve bu durum, bazı alanlardaki uygulamalarını engelleyebilmektedir. Özellikle geliştiriciler, çözümlerini farklı kütüphaneler, diller ve platformlar arasında entegre etmek zorunda kaldıklarında, makine öğrenmesi uygulamalarının etkinliği azalabilmektedir. Bu çalışma, uzman değerlendirmelerine dayanarak, çeşitli faktörlerin makine öğrenmesi kütüphanelerinin başarısı üzerindeki doğrudan ve dolaylı etkilerini incelemektedir. Zira kullanıcı deneyimlerine dayalı olarak kütüphane geliştirimini şekillendiren kritik faktörlere odaklanmak, stratejik ilerleme sağlamak ve enerji ile kaynak kullanımını optimize etmek açısından büyük önem taşımaktadır. Bu faktörlerin çoğu insan algısına bağlı belirsizlikler içerdiğinden, yöntem olarak z-sayılarla birlikte bulanık dilsel bir yaklaşım benimsenmiştir. Bulgular, faktörler arasındaki karşılıklı ilişkilerin dikkate alınmasının, onların önem derecelerini önemli ölçüde değiştirdiğini ortaya koymuştur; zira bu yaklaşım hem doğrudan hem de dolaylı etkileri hesaba katmaktadır. Ayrıca bu ilişkiler, hangi faktörlerin stratejik olarak önceliklendirilmesi gerektiğini de vurgulamaktadır; çünkü bir faktördeki iyileşme, diğerlerinde de gelişmeleri tetikleyebilir. Elde edilen sonuçlar, yapay zekâ kütüphanelerini geliştiren topluluğun doğru hedeflere yönelmesine ve yapay zekâ dönüşümünün sürdürülebilirliğini sağlamak için etkili stratejiler formüle etmesine katkı sağlayabilir. 

Anahtar Kelimeler

• Yapay zekâ
• Bulanık mantık
• Dilsel terim kümesi
• Makine öğrenmesi kütüphaneleri
• Z-sayısı

Kaynakça

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