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Dergiler / Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering / 2017 / Cilt: 18 - Sayı: 3

Robust Principal Component Analysis based on Fuzzy Coded Data

B. Barış ALKAN
Sevgi GANIK
Sayfa
754–762
Yayın Tarihi
2017-09-30
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

In light of the study's findings, it is seen that the proposed approach gives better results than the ones in the classical and robust principal component analysis in the presence of outliers in dataset.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:In the presence of outliers in the dataset, the principal component analysis method, like many of the classical statistical methods, is severely affected.
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Temel Bulgular & Veri:The performance of proposed approach called robust principal component analysis based on fuzzy coded data is examined through a set of artificial dataset that are generated by considering three different scenarios and a real dataset to observe how it is affected by the increase in sample size and changes in the rate of outliers.
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Sonuç & Katkı:In light of the study's findings, it is seen that the proposed approach gives better results than the ones in the classical and robust principal component analysis in the presence of outliers in dataset.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Fuzzy coded data · Outliers

Abstract

In the presence of outliers in the dataset, the principal component analysis method, like many of the classical statistical methods, is severely affected. For this reason, if there are outliers in dataset, researchers tend to use alternative methods. Use of fuzzy and robust approaches is the leading choice among these methods. In this study, a new approach to robust fuzzy principal component analysis is proposed. This approach combines the power of both robust and fuzzy methods at the same time and collects these two approaches under the framework of principal component analysis. The performance of proposed approach called robust principal component analysis based on fuzzy coded data is examined through a set of artificial dataset that are generated by considering three different scenarios and a real dataset to observe how it is affected by the increase in sample size and changes in the rate of outliers. In light of the study's findings, it is seen that the proposed approach gives better results than the ones in the classical and robust principal component analysis in the presence of outliers in dataset.

Anahtar kelimeler
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Bu Makaleye Atıf Yap

ALKAN, B. B., GANIK, S. (2017). Robust Principal Component Analysis based on Fuzzy Coded Data. Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering, Cilt: 18 - Sayı: 3, 754–762. https://ajindex.com/articles/196929

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Kaynakça (13)

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