Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Yuanzi Zhang"'
Publikováno v:
Algorithms, Vol 14, Iss 11, p 324 (2021)
There are generally many redundant and irrelevant features in high-dimensional datasets, which leads to the decline of classification performance and the extension of execution time. To tackle this problem, feature selection techniques are used to sc
Externí odkaz:
https://doaj.org/article/4684a31a5083410dacbff9c122c956ce
Publikováno v:
Algorithms, Vol 14, Iss 4, p 120 (2021)
Quantitative Structure–Activity Relationship (QSAR) aims to correlate molecular structure properties with corresponding bioactivity. Chance correlations and multicollinearity are two major problems often encountered when generating QSAR models. Fea
Externí odkaz:
https://doaj.org/article/d71886562e47437fba4ad618658f93b5
Publikováno v:
Soft Computing. 26:9665-9687
Feature selection is an important data preprocessing method in data mining and machine learning, yet it faces the challenge of “curse of dimensionality” when dealing with high-dimensional data. In this paper, a self-adaptive level-based learning
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f4afd6d61e3f9d69919901121f2d9104
https://doi.org/10.1007/s00500-022-06826-1
https://doi.org/10.1007/s00500-022-06826-1
Publikováno v:
Algorithms, Vol 14, Iss 324, p 324 (2021)
Algorithms
Volume 14
Issue 11
Algorithms
Volume 14
Issue 11
There are generally many redundant and irrelevant features in high-dimensional datasets, which leads to the decline of classification performance and the extension of execution time. To tackle this problem, feature selection techniques are used to sc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b31ae7d021c176c80b863ac3cb238b13
https://www.mdpi.com/1999-4893/14/11/324
https://www.mdpi.com/1999-4893/14/11/324
Publikováno v:
Engineering Applications of Artificial Intelligence. 114:105088
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b59feaabe959676abd32cec06f131fe7
https://doi.org/10.1016/j.engappai.2022.105088
https://doi.org/10.1016/j.engappai.2022.105088
Publikováno v:
Algorithms
Volume 14
Issue 4
Algorithms, Vol 14, Iss 120, p 120 (2021)
Volume 14
Issue 4
Algorithms, Vol 14, Iss 120, p 120 (2021)
Quantitative Structure–Activity Relationship (QSAR) aims to correlate molecular structure properties with corresponding bioactivity. Chance correlations and multicollinearity are two major problems often encountered when generating QSAR models. Fea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6027bc3d223906d15f8cde891db77710
https://doi.org/10.3390/a14040120
https://doi.org/10.3390/a14040120