TY  - JOUR
T1  - Makine Öğrenimi Teknikleriyle Uyku Bozukluklarına Yönelik Derinlemesine Analiz ve Sınıflandırma
TT  - In-depth Analysis and Classification of Sleep Disorders with Machine Learning Techniques
AU  - Gür, Yunus Emre
AU  - Solak, Bilal
AU  - Toğaçar, Mesut
PY  - 2024
DA  - June
Y2  - 2024
DO  - 10.29132/ijpas.1475183
JF  - International Journal of Pure and Applied Sciences
PB  - Munzur Üniversitesi
WT  - DergiPark
SN  - 2149-0910
SP  - 242
EP  - 260
VL  - 10
IS  - 1
LA  - tr
AB  - Bu çalışma, uyku kalitesi ile yaşam tarzı faktörleri arasındaki bağlantıyı derinleme-sine incelemektedir. Araştırma, cinsiyet, yaş ve meslek gibi demografik özellikler ile uyku süresi, kalitesi, fiziksel aktivite düzeyleri ve stres gibi yaşam tarzı değişken-lerinin uyku bozukluklarına etkisini makine öğrenimi teknikleri kullanarak analiz etmektedir. Çalışmada, Lojistik Regresyon, En yakın komşular, Naive Bayes, Rastgele Orman, AdaBoostClassifier ve Destek Vektör Makinesi (SVM) gibi çeşitli makine öğrenimi modelleri uygulanmıştır. Özellikle Rastgele Orman ve SVM mod-elleri, yüksek doğruluk oranları sayesinde uyku bozukluklarını belirlemede etkili oldukları gözlemlenmiştir. Ayrıca, meslek ve stres düzeyleri ile uyku bozuklukları arasındaki ilişkiler üzerine detaylı analizler yapılarak, uyku sağlığının iyileştirilmesi için öneriler sunulmuştur.
KW  - Uyku sağlığı
KW  - Uyku bozuklukları
KW  - Makine öğrenimi
KW  - Random Forest
KW  - Destek Vektör Makinesi
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UR  - https://doi.org/10.29132/ijpas.1475183
L1  - https://dergipark.org.tr/tr/download/article-file/3892055
ER  -