A learning-based demand classification service with using XGBoost in institutional area
Başlık:
A learning-based demand classification service with using XGBoost in institutional area
Yazar:
Gürakın, Çağrı, author.
Yazar Ek Girişi:
Fiziksel Tanımlama:
xii, 49 leaves: illustrarions, charts;+ 1 computer laser optical disc.
Özet:
This study, purposes to explain the development stages and methodology of data classification service that has a text-based adaptable programming interface. One of the successful classification algorithms, XGBoost, was preferred in the study. The dataset that is used in the study obtained by 'Digital Business Tracking Application' of a name anonymized company. The dataset is tested by using different classification algorithms and detailed performance evaluation was conducted. As a result, highest accuracy rate is obtained with 'Data Classification Service' which was developed by using XGBoost algorithm.
Yazar Ek Girişi:
Tüzel Kişi Ek Girişi:
Tek Biçim Eser Adı:
Thesis (Master)--İzmir Institute of Technology: Computer Engineering.
İzmir Institute of Technology: Computer Engineering--Thesis (Master).
Elektronik Erişim:
Access to Electronic Versiyon.