An Algebraic Approach to Clustering and Classification with Support Vector Machiness
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Tarih
2022
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
MDPI
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
In this note, we propose a novel classification approach by introducing a new clustering method, which is used as an intermediate step to discover the structure of a data set. The proposed clustering algorithm uses similarities and the concept of a clique to obtain clusters, which can be used with different strategies for classification. This approach also reduces the size of the training data set. In this study, we apply support vector machines (SVMs) after obtaining clusters with the proposed clustering algorithm. The proposed clustering algorithm is applied with different strategies for applying SVMs. The results for several real data sets show that the performance is comparable with the standard SVM while reducing the size of the training data set and also the number of support vectors. © 2022 by the authors Licensee MDPI, Basel, Switzerland.
Açıklama
Anahtar Kelimeler
Algebraic statistics; Classification; Clique; Clustering; Machine learning; Support vector machine
Kaynak
Mathematics
WoS Q Değeri
Scopus Q Değeri
Q1
Cilt
10
Sayı
1
