Hierarchical Multi Twin Support Vector Machine
Tập 130 Số 2B (2021), Bài nghiên cứu
Tập 130 Số 2B (2021)

Hierarchical Multi Twin Support Vector Machine

Bài nghiên cứu
https://doi.org/10.26459/hueunijtt.v130i2B.5829
Đã xuất bản 2021-07-07
Nguyen The Cuong
Trường Đại học Thông tin Liên lạc

Tóm tắt

In binary classification problems, two classes normally have different tendencies. More complex, the clusters in each class also tend to be different. Traditional algorithms as Support Vector Machine (SVM) or Twin Support Vector Machine (TWSVM) don't sufficiently exploit structural information with cluster granularity of the data, cause of restricts the capability of simulation of data trends. Structural twin support vector machine (S-TWSVM) sufficiently exploits structural information with cluster granularity of one class for learning a represented hyperplane of that class. This makes S-TWSVM's data simulation capabilities better than TWSVM. However, for the data type that each class consists of clusters of different trends, the capability of simulation of S-TWSVM is restricted. In this paper, we propose a new Hierarchical Multi Twin Support Vector Machine (called HM-TWSVM) for classification problem with each cluster-vs-class strategy. HM-TWSVM overcomes the limitations of S-TWSVM. Experiment results show that HM-TWSVM could describe the tendency of each cluster.
https://doi.org/10.26459/hueunijtt.v130i2B.5829
Forth Coming Paper (English)

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