A Binary Classification Model for PM 10 Levels

Kiymet Kaya, Sule Gunduz Oguducu

Araştırma sonucu: ???type-name???Konferans katkısıbilirkişi

6 Atıf (Scopus)

Özet

The particulate matter in the air effects human health in a negative way. Yet, no regression model has estimated the density of PM 10 at Istanbul using datasets with imbalanced class distribution. In order to fill this gap, we designed a new regression model that transforms the regression problem into the imbalanced binary classification problem at the initial stage. In this paper, PM 10 classification problem is considered as the imbalanced binary classification problem that is coded as harmless class (1) and dangerous class (0). In the sampling part of the solution, the balanced version of the data by Under Sampling methods yielded unsatisfactory results. In the algorithmic part, the performances of RFC (Random Forest Classifier), ETC (Extra Trees Classifier) and GBC (Gradient Boosting Classifier) models, which stand out with their positive effects on unbalanced learning problems, are compared in terms of AUROC. The proposed model, uses all training set samples and predicts through RFC. The experimental results on real world dataset seem quite promising for our further research.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığıUBMK 2018 - 3rd International Conference on Computer Science and Engineering
YayınlayanInstitute of Electrical and Electronics Engineers Inc.
Sayfalar361-366
Sayfa sayısı6
ISBN (Elektronik)9781538678930
DOI'lar
Yayın durumuYayınlandı - 6 Ara 2018
Etkinlik3rd International Conference on Computer Science and Engineering, UBMK 2018 - Sarajevo, Bosnia and Herzegovina
Süre: 20 Eyl 201823 Eyl 2018

Yayın serisi

AdıUBMK 2018 - 3rd International Conference on Computer Science and Engineering

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???3rd International Conference on Computer Science and Engineering, UBMK 2018
Ülke/BölgeBosnia and Herzegovina
ŞehirSarajevo
Periyot20/09/1823/09/18

Bibliyografik not

Publisher Copyright:
© 2018 IEEE.

Finansman

ACKNOWLEDGMENT We’re thankful to the Turkish State Meteorological Service for providing the meteorological data used in this study. The first author was partially supported by the ITU project of standardization, integration and modernization of measuring systems.

FinansörlerFinansör numarası
International Technological University

    Parmak izi

    A Binary Classification Model for PM 10 Levels' araştırma başlıklarına git. Birlikte benzersiz bir parmak izi oluştururlar.

    Alıntı Yap