A learning-based demand classification service with using XGBoost in institutional area
tarafından
Gürakın, Çağrı, author.
Başlık
:
A learning-based demand classification service with using XGBoost in institutional area
Yazar
:
Gürakın, Çağrı, author.
Yazar Ek Girişi
:
Gürakın, Çağrı, author.
Fiziksel Tanımlama
:
xii, 49 leaves: illustrarions, charts;+ 1 computer laser optical disc.
Özet
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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.
Konu Başlığı
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Natural language processing (Computer science).
Machine learning.
Supervised learning (Machine learning).
Yazar Ek Girişi
:
Ayav, Tolga,
Tüzel Kişi Ek Girişi
:
İzmir Institute of Technology. Computer Engineering.
Tek Biçim Eser Adı
:
Thesis (Master)--İzmir Institute of Technology: Computer Engineering.
İzmir Institute of Technology: Computer Engineering--Thesis (Master).
Elektronik Erişim
:
Library | Materyal Türü | Demirbaş Numarası | Yer Numarası | Durumu/İade Tarihi |
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IYTE Library | Tez | T001926 | QA76.9.N38 G97 2019 | Tez Koleksiyonu |