TY  - JOUR
T1  - KarcıFANN Yönteminde Ağırlık Sönümlemenin Etkisi
TT  - The Effect of Weight Decay in the KarcıFANN Method
AU  - Karakurt, Meral
PY  - 2025
DA  - December
Y2  - 2025
DO  - 10.53070/bbd.1809030
JF  - Computer Science
JO  - JCS
PB  - Ali KARCI
WT  - DergiPark
SN  - 2548-1304
SP  - 201
EP  - 216
VL  - 10
IS  - 2
LA  - tr
AB  - Yapay sinir ağlarının (YSA) modellenmesinde, optimizasyon yöntemi, aktivasyon ve hata fonksiyonu gibi hiperparametrelerle birlikte çeşitli düzenleme (düzenlileştirme) yöntemleri kullanılmaktadır.  Bu yöntemlerden biri olan ağırlık sönümleme işlemi, modellerin eğitimi aşamasında ağırlık vektörlerinin çok fazla büyümesiyle ortaya çıkan gradyan patlaması ve ezberleme gibi önemli problemlerin çözülmesi ve modellerin genelleme performanslarının artırılması amacıyla uygulanmaktadır. Bu çalışmada, ağırlık sönümleme hiperparametresinin, KarcıFANN yönteminin performansına etkileri analiz edilmektedir. Bu amaçla, KarcıFANN yöntemi ile tasarlanan çeşitli modellere ağırlık sönümleme işlemi uygulanmıştır. MNIST ve Dry Bean veri setlerinin sınıflandırılması sonucu elde edilen bulgular, ağırlık sönümleme hiperparametresinin, modellerin başarımını ve genelleme kabiliyetini önemli ölçüde iyileştirdiğini göstermiştir.
KW  - KarcıFANN
KW  - sınıflandırma
KW  - düzenleme yöntemleri
KW  - ağırlık sönümleme
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UR  - https://doi.org/10.53070/bbd.1809030
L1  - https://dergipark.org.tr/en/download/article-file/5354388
ER  -