A High-Dimensional Modeling System Based on Analytical Hierarchy Process and Information Criteria
High-dimensional data sets frequently occur in several scientific areas, and special techniques are required to analyze these types of data sets. Especially, it becomes important to apply a suitable model in classification problems. In this study, a novel approach is proposed to estimate a statistic...
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Published in | Mathematical problems in engineering Vol. 2021; pp. 1 - 9 |
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Main Author | |
Format | Journal Article |
Language | English |
Published |
New York
Hindawi
2021
Hindawi Limited |
Subjects | |
Online Access | Get full text |
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Summary: | High-dimensional data sets frequently occur in several scientific areas, and special techniques are required to analyze these types of data sets. Especially, it becomes important to apply a suitable model in classification problems. In this study, a novel approach is proposed to estimate a statistical model for high-dimensional data sets. The proposed method uses analytical hierarchical process (AHP) and information criteria for determining the optimal PCs for the classification model. The high-dimensional “colon” and “gravier” datasets were used in evaluation part. Application results demonstrate that the proposed approach can be successfully used for modeling purposes. |
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ISSN: | 1024-123X 1563-5147 |
DOI: | 10.1155/2021/6198317 |