A copula-based classification using  agglomerated feature selection_extraction: an application in cervical cancer diagnostic

Necla Koçhan; Ayyub Sheikhi

Makale detayları

A copula-based classification using agglomerated feature selection_extraction: an application in cervical cancer diagnostic

Yazarlar:

Necla Koçhan | Ayyub Sheikhi

Yayıncı:

Ankara University

Ana Başlıklar:

Biostatistics | Computational Statistics

Dergi:

Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics Vol.74 Issue 3, pp.492-502

Belge Tipi:

Makale

Yayın Tarihi:

9/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001357872

pISSN:

1303-5991

Anahtar kelimeler:

Özet:

 The use of gene-expression datasets has significantly enhanced our understanding of complex diseases such as cancer. The importance of the relationship between genes in analyzing such datasets has been highlighted, indicating their crucial role in diagnosing the disease accurately. In this study, we investigate the associated copulas between attributes to extract fundamental block-related components. Subsequently, we perform a classification algorithm based on these components to classify a labeled target variable. Specifically, examining the practical implications and effectiveness of our approach in real-world scenarios, we provide a novel illustrative application in cervical cancer classification.

 The use of gene-expression datasets has significantly enhanced our understanding of complex diseases such as cancer. The importance of the relationship between genes in analyzing such datasets has been highlighted, indicating their crucial role in diagnosing the disease accurately. In this study, we investigate the associated copulas between attributes to extract fundamental block-related components. Subsequently, we perform a classification algorithm based on these components to classify a labeled target variable. Specifically, examining the practical implications and effectiveness of our approach in real-world scenarios, we provide a novel illustrative application in cervical cancer classification.

 The use of gene-expression datasets has significantly enhanced our understanding of complex diseases such as cancer. The importance of the relationship between genes in analyzing such datasets has been highlighted, indicating their crucial role in diagnosing the disease accurately. In this study, we investigate the associated copulas between attributes to extract fundamental block-related components. Subsequently, we perform a classification algorithm based on these components to classify a labeled target variable. Specifically, examining the practical implications and effectiveness of our approach in real-world scenarios, we provide a novel illustrative application in cervical cancer classification.

 The use of gene-expression datasets has significantly enhanced our understanding of complex diseases such as cancer. The importance of the relationship between genes in analyzing such datasets has been highlighted, indicating their crucial role in diagnosing the disease accurately. In this study, we investigate the associated copulas between attributes to extract fundamental block-related components. Subsequently, we perform a classification algorithm based on these components to classify a labeled target variable. Specifically, examining the practical implications and effectiveness of our approach in real-world scenarios, we provide a novel illustrative application in cervical cancer classification.

Makale detayları

A copula-based classification using agglomerated feature selection_extraction: an application in cervical cancer diagnostic

Yazarlar:

Necla Koçhan | Ayyub Sheikhi

Yayıncı:

Ankara University

Ana Başlıklar:

Biostatistics | Computational Statistics

Dergi:

Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics Vol.74 Issue 3, pp.492-502

Belge Tipi:

Makale

Yayın Tarihi:

9/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001357872

pISSN:

1303-5991

Copula

classification

feature selection

feature extraction

association measures

gene-expression

Sayı

Makale detayları

A copula-based classification using agglomerated feature selection_extraction: an application in cervical cancer diagnostic

Yazarlar: Necla Koçhan | Ayyub Sheikhi

Yayıncı: Ankara University

Ana Başlıklar: Biostatistics | Computational Statistics

Dergi: Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics Vol.74 Issue 3, pp.492-502

Belge Tipi: Makale

Yayın Tarihi: 9/2025

Belge Dili: İngilizce

Document ID (Org No.): 2001357872

pISSN: 1303-5991

Copula

classification

feature selection

feature extraction

association measures

gene-expression

Sayı

Yazarlar:

Necla Koçhan | Ayyub Sheikhi

Yayıncı:

Ankara University

Ana Başlıklar:

Biostatistics | Computational Statistics

Dergi:

Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics Vol.74 Issue 3, pp.492-502

Belge Tipi:

Makale

Yayın Tarihi:

9/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001357872

pISSN:

1303-5991