A harmony search algorithm for clustering with feature selection
This paper presents a new clustering algorithm, called IHSK, with feature selection in a linear order of complexity. The algorithm is based on the combination of the harmony search and K-means algorithms. Feature selection uses both the concept of variability and a heuristic method that penalizes t...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Universidad de Antioquia
2013-03-01
|
| Series: | Revista Facultad de Ingeniería Universidad de Antioquia |
| Subjects: | |
| Online Access: | https://revistas.udea.edu.co/index.php/ingenieria/article/view/14724 |
| _version_ | 1797861649677287424 |
|---|---|
| author | Carlos Cobos Elizabeth León Martha Mendoza |
| author_facet | Carlos Cobos Elizabeth León Martha Mendoza |
| author_sort | Carlos Cobos |
| collection | DOAJ |
| description |
This paper presents a new clustering algorithm, called IHSK, with feature selection in a linear order of complexity. The algorithm is based on the combination of the harmony search and K-means algorithms. Feature selection uses both the concept of variability and a heuristic method that penalizes the presence of dimensions with a low probability of contributing to the current solution. The algorithm was tested with sets of synthetic and real data, obtaining promising results.
|
| first_indexed | 2024-04-09T22:07:40Z |
| format | Article |
| id | doaj.art-d98f9754a0b748798453a3fe9781f71c |
| institution | Directory Open Access Journal |
| issn | 0120-6230 2422-2844 |
| language | English |
| last_indexed | 2024-04-09T22:07:40Z |
| publishDate | 2013-03-01 |
| publisher | Universidad de Antioquia |
| record_format | Article |
| series | Revista Facultad de Ingeniería Universidad de Antioquia |
| spelling | doaj.art-d98f9754a0b748798453a3fe9781f71c2023-03-23T12:35:46ZengUniversidad de AntioquiaRevista Facultad de Ingeniería Universidad de Antioquia0120-62302422-28442013-03-015510.17533/udea.redin.14724A harmony search algorithm for clustering with feature selectionCarlos Cobos0Elizabeth León1Martha Mendoza2University of CaucaNational University of ColombiaUniversity of Cauca This paper presents a new clustering algorithm, called IHSK, with feature selection in a linear order of complexity. The algorithm is based on the combination of the harmony search and K-means algorithms. Feature selection uses both the concept of variability and a heuristic method that penalizes the presence of dimensions with a low probability of contributing to the current solution. The algorithm was tested with sets of synthetic and real data, obtaining promising results. https://revistas.udea.edu.co/index.php/ingenieria/article/view/14724harmony searchclusteringfeature selection |
| spellingShingle | Carlos Cobos Elizabeth León Martha Mendoza A harmony search algorithm for clustering with feature selection Revista Facultad de Ingeniería Universidad de Antioquia harmony search clustering feature selection |
| title | A harmony search algorithm for clustering with feature selection |
| title_full | A harmony search algorithm for clustering with feature selection |
| title_fullStr | A harmony search algorithm for clustering with feature selection |
| title_full_unstemmed | A harmony search algorithm for clustering with feature selection |
| title_short | A harmony search algorithm for clustering with feature selection |
| title_sort | harmony search algorithm for clustering with feature selection |
| topic | harmony search clustering feature selection |
| url | https://revistas.udea.edu.co/index.php/ingenieria/article/view/14724 |
| work_keys_str_mv | AT carloscobos aharmonysearchalgorithmforclusteringwithfeatureselection AT elizabethleon aharmonysearchalgorithmforclusteringwithfeatureselection AT marthamendoza aharmonysearchalgorithmforclusteringwithfeatureselection AT carloscobos harmonysearchalgorithmforclusteringwithfeatureselection AT elizabethleon harmonysearchalgorithmforclusteringwithfeatureselection AT marthamendoza harmonysearchalgorithmforclusteringwithfeatureselection |