دورية أكاديمية
A Novel Nonparametric Feature Selection Approach Based on Mutual Information Transfer Network
| العنوان: | A Novel Nonparametric Feature Selection Approach Based on Mutual Information Transfer Network |
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| المؤلفون: | Kunmei Li, Nasser Fard |
| المصدر: | Entropy, Vol 24, Iss 9, p 1255 (2022) |
| بيانات النشر: | MDPI AG, 2022. |
| سنة النشر: | 2022 |
| المجموعة: | LCC:Science LCC:Astrophysics LCC:Physics |
| مصطلحات موضوعية: | feature selection, mutual information, linear programming, maxflow, P-median problem, Science, Astrophysics, QB460-466, Physics, QC1-999 |
| الوصف: | The filter feature selection algorithm is habitually used as an effective way to reduce the computational cost of data analysis by selecting and implementing only a subset of original features into the study. Mutual information (MI) is a popular measurement adopted to quantify the dependence among features. MI-based greedy forward methods (MIGFMs) have been widely applied to escape from computational complexity and exhaustion of high-dimensional data. However, most MIGFMs are parametric methods that necessitate proper preset parameters and stopping criteria. Improper parameters may lead to ignorance of better results. This paper proposes a novel nonparametric feature selection method based on mutual information and mixed-integer linear programming (MILP). By forming a mutual information network, we transform the feature selection problem into a maximum flow problem, which can be solved with the Gurobi solver in a reasonable time. The proposed method attempts to prevent negligence on obtaining a superior feature subset while keeping the computational cost in an affordable range. Analytical comparison of the proposed method with six feature selection methods reveals significantly better results compared to MIGFMs, considering classification accuracy. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1099-4300 |
| Relation: | https://www.mdpi.com/1099-4300/24/9/1255; https://doaj.org/toc/1099-4300 |
| DOI: | 10.3390/e24091255 |
| URL الوصول: | https://doaj.org/article/9b8070229ce24357be78e936dcc2e452 |
| رقم الأكسشن: | edsdoj.9b8070229ce24357be78e936dcc2e452 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 10994300 |
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| DOI: | 10.3390/e24091255 |