New Classifier Ensemble and Fuzzy Community Detection Methods Using POP Choquet-like Integrals
Among various data analysis methods, classifier ensemble (data classification) and community network detection (data clustering) have aroused the interest of many scholars. The maximum operator, as the fusion function, was always used to fuse the results of the base algorithms in the classifier ense...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Fractal and Fractional |
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| Online Access: | https://www.mdpi.com/2504-3110/7/8/588 |
| _version_ | 1797584736447627264 |
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| author | Xiaohong Zhang Haojie Jiang Jingqian Wang |
| author_facet | Xiaohong Zhang Haojie Jiang Jingqian Wang |
| author_sort | Xiaohong Zhang |
| collection | DOAJ |
| description | Among various data analysis methods, classifier ensemble (data classification) and community network detection (data clustering) have aroused the interest of many scholars. The maximum operator, as the fusion function, was always used to fuse the results of the base algorithms in the classifier ensemble and the membership degree of nodes to classes in the fuzzy community. It is vital to use generalized fusion functions in ensemble and community applications. Since the Pseudo overlap function and the Choquet-like integrals are two new fusion functions, they can be combined as a more generalized fusion function. Along this line, this paper presents new classifier ensemble and fuzzy community detection methods using a pseudo overlap pair (POP) Choquet-like integral (expressed as a fraction). First, the pseudo overlap function pair is proposed to replace the product operator of the Choquet integral. Then, the POP Choquet-like integrals are defined to perform the combinatorial step of ensembles of classifiers and to generalize the GN modularity for the fuzzy community network. Finally, two new algorithms are designed for experiments, and some computational experiments with other algorithms show the importance of POP Choquet-like integrals. All of the experimental results show that our algorithms are practical. |
| first_indexed | 2024-03-10T23:55:52Z |
| format | Article |
| id | doaj.art-fcf023b469fb4e72ae65f1afb85c9069 |
| institution | Directory Open Access Journal |
| issn | 2504-3110 |
| language | English |
| last_indexed | 2024-03-10T23:55:52Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Fractal and Fractional |
| spelling | doaj.art-fcf023b469fb4e72ae65f1afb85c90692023-11-19T01:11:04ZengMDPI AGFractal and Fractional2504-31102023-07-017858810.3390/fractalfract7080588New Classifier Ensemble and Fuzzy Community Detection Methods Using POP Choquet-like IntegralsXiaohong Zhang0Haojie Jiang1Jingqian Wang2School of Mathematics and Data Science, Shaanxi University of Science and Technology, Xi’an 710016, ChinaSchool of Mathematics and Data Science, Shaanxi University of Science and Technology, Xi’an 710016, ChinaSchool of Mathematics and Data Science, Shaanxi University of Science and Technology, Xi’an 710016, ChinaAmong various data analysis methods, classifier ensemble (data classification) and community network detection (data clustering) have aroused the interest of many scholars. The maximum operator, as the fusion function, was always used to fuse the results of the base algorithms in the classifier ensemble and the membership degree of nodes to classes in the fuzzy community. It is vital to use generalized fusion functions in ensemble and community applications. Since the Pseudo overlap function and the Choquet-like integrals are two new fusion functions, they can be combined as a more generalized fusion function. Along this line, this paper presents new classifier ensemble and fuzzy community detection methods using a pseudo overlap pair (POP) Choquet-like integral (expressed as a fraction). First, the pseudo overlap function pair is proposed to replace the product operator of the Choquet integral. Then, the POP Choquet-like integrals are defined to perform the combinatorial step of ensembles of classifiers and to generalize the GN modularity for the fuzzy community network. Finally, two new algorithms are designed for experiments, and some computational experiments with other algorithms show the importance of POP Choquet-like integrals. All of the experimental results show that our algorithms are practical.https://www.mdpi.com/2504-3110/7/8/588data analysispseudo overlap functionChoquet-like integralclassifier ensemblecommunity network detection |
| spellingShingle | Xiaohong Zhang Haojie Jiang Jingqian Wang New Classifier Ensemble and Fuzzy Community Detection Methods Using POP Choquet-like Integrals Fractal and Fractional data analysis pseudo overlap function Choquet-like integral classifier ensemble community network detection |
| title | New Classifier Ensemble and Fuzzy Community Detection Methods Using POP Choquet-like Integrals |
| title_full | New Classifier Ensemble and Fuzzy Community Detection Methods Using POP Choquet-like Integrals |
| title_fullStr | New Classifier Ensemble and Fuzzy Community Detection Methods Using POP Choquet-like Integrals |
| title_full_unstemmed | New Classifier Ensemble and Fuzzy Community Detection Methods Using POP Choquet-like Integrals |
| title_short | New Classifier Ensemble and Fuzzy Community Detection Methods Using POP Choquet-like Integrals |
| title_sort | new classifier ensemble and fuzzy community detection methods using pop choquet like integrals |
| topic | data analysis pseudo overlap function Choquet-like integral classifier ensemble community network detection |
| url | https://www.mdpi.com/2504-3110/7/8/588 |
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