Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Yuefeng Zheng"'
Publikováno v:
IEEE Access, Vol 12, Pp 106236-106252 (2024)
Feature selection plays a significant role in machine learning and data mining, where the goal is to screen out the most representative and relevant subset of features from a large collection of features to improve the performance and generalization
Externí odkaz:
https://doaj.org/article/15c4d75931ee44af9506d7e272d5cccb
Publikováno v:
IEEE Access, Vol 8, Pp 155619-155629 (2020)
Feature selection, which eliminates irrelevant and redundant features, is one of the most efficient classification methods. However, searching for an optimal subset from the original set is still a challenging problem. This paper proposes a novel fea
Externí odkaz:
https://doaj.org/article/4fda6457c78741ae8c8c3f258078c16b
Publikováno v:
IEEE Access, Vol 7, Pp 14908-14923 (2019)
Feature selection enhances classification accuracy by removing irrelevant and redundant feature. Feature selection plays an important role in data mining and pattern recognition. In this paper, we propose a hybrid feature subset selection algorithm c
Externí odkaz:
https://doaj.org/article/f47fa6040fca439a8acd622b11303b57
Publikováno v:
IEEE Access, Vol 8, Pp 155619-155629 (2020)
Feature selection, which eliminates irrelevant and redundant features, is one of the most efficient classification methods. However, searching for an optimal subset from the original set is still a challenging problem. This paper proposes a novel fea
Publikováno v:
IEEE Access, Vol 7, Pp 14908-14923 (2019)
Feature selection enhances classification accuracy by removing irrelevant and redundant feature. Feature selection plays an important role in data mining and pattern recognition. In this paper, we propose a hybrid feature subset selection algorithm c
Publikováno v:
Electronics. 11:2200
The convergence of blockchain with the internet of things (IoT) attracted widespread attention. Blockchain mainly solved the problem of secure storage and trusted transactions. The convergence of these two emerging technologies enhanced the security
Autor:
Yuefeng Zheng, Ying Liu
Publikováno v:
Emerging Trends in Intelligent and Interactive Systems and Applications ISBN: 9783030637835
Aiming at the current network security problems, we propose a network attack recognition method based on probability target graph. Based on the target graph, this method replaces the state nodes with the target nodes and adds the observation nodes, a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::caba48f8ea194d9de380bdbce131f36d
https://doi.org/10.1007/978-3-030-63784-2_96
https://doi.org/10.1007/978-3-030-63784-2_96
Publikováno v:
The Journal of Supercomputing. 76:3494-3526
For each microarray data set, only a small number of genes are beneficial. Due to the high-dimensional problem, gene selection research work remains a challenge. In order to solve the high-dimensional problem, we propose a dimensionality reduction al
Publikováno v:
Personal and Ubiquitous Computing. 22:971-985
Feature selection is an important filtering method for data analysis, pattern classification, data mining, and so on. Feature selection reduces the number of features by removing irrelevant and redundant data. In this paper, we propose a hybrid filte
Publikováno v:
Expert Systems with Applications. 83:1-17
ACBFO and ISEDBFO are proposed based on original bacterial foraging optimization.The modified chemotaxis step raises selected probability of primary features in ACBFO.Swarming equation and elimination dispersal step are improved in ISEDBFO.ACBFO and