Journal article 119 views
Sparse supervised principal component analysis (SSPCA) for dimension reduction and variable selection
Engineering Applications of Artificial Intelligence, Volume: 65, Pages: 168 - 177
Swansea University Author:
Sara Sharifzadeh
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DOI (Published version): 10.1016/j.engappai.2017.07.004
Abstract
Sparse supervised principal component analysis (SSPCA) for dimension reduction and variable selection
Published in: | Engineering Applications of Artificial Intelligence |
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ISSN: | 0952-1976 |
Published: |
Elsevier BV
2017
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URI: | https://cronfa.swan.ac.uk/Record/cronfa65607 |
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v2 65607 2024-02-09 Sparse supervised principal component analysis (SSPCA) for dimension reduction and variable selection a4e15f304398ecee3f28c7faec69c1b0 0000-0003-4621-2917 Sara Sharifzadeh Sara Sharifzadeh true false 2024-02-09 SCS Journal Article Engineering Applications of Artificial Intelligence 65 168 177 Elsevier BV 0952-1976 Variable selection; Dimension reduction; Sparse PCA; Supervised PCA; Sparse supervised PCA; Penalized matrix decomposition 1 10 2017 2017-10-01 10.1016/j.engappai.2017.07.004 COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University This work was (in part) financed by the Centre for Imaging Food Quality project which is funded by the Danish Council for Strategic Research (contract No. 09-067039) within the Program Commission on Health, Food and Welfare. 2024-04-04T12:46:44.0688280 2024-02-09T01:16:42.5473395 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Sara Sharifzadeh 0000-0003-4621-2917 1 Ali Ghodsi 2 Line H. Clemmensen 3 Bjarne K. Ersbøll 4 |
title |
Sparse supervised principal component analysis (SSPCA) for dimension reduction and variable selection |
spellingShingle |
Sparse supervised principal component analysis (SSPCA) for dimension reduction and variable selection Sara Sharifzadeh |
title_short |
Sparse supervised principal component analysis (SSPCA) for dimension reduction and variable selection |
title_full |
Sparse supervised principal component analysis (SSPCA) for dimension reduction and variable selection |
title_fullStr |
Sparse supervised principal component analysis (SSPCA) for dimension reduction and variable selection |
title_full_unstemmed |
Sparse supervised principal component analysis (SSPCA) for dimension reduction and variable selection |
title_sort |
Sparse supervised principal component analysis (SSPCA) for dimension reduction and variable selection |
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a4e15f304398ecee3f28c7faec69c1b0 |
author_id_fullname_str_mv |
a4e15f304398ecee3f28c7faec69c1b0_***_Sara Sharifzadeh |
author |
Sara Sharifzadeh |
author2 |
Sara Sharifzadeh Ali Ghodsi Line H. Clemmensen Bjarne K. Ersbøll |
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Journal article |
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Engineering Applications of Artificial Intelligence |
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65 |
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168 |
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2017 |
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Swansea University |
issn |
0952-1976 |
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10.1016/j.engappai.2017.07.004 |
publisher |
Elsevier BV |
college_str |
Faculty of Science and Engineering |
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|
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facultyofscienceandengineering |
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Faculty of Science and Engineering |
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facultyofscienceandengineering |
hierarchy_parent_title |
Faculty of Science and Engineering |
department_str |
School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science |
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published_date |
2017-10-01T12:46:40Z |
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11.021648 |