Extraction of prototype-based threshold rules using neural training procedure
Complex neural and machine learning algorithms usually lack comprehensibility. Combination of sequential covering with prototypes based on threshold neurons leads to a prototype-threshold based rule system. This kind of knowledge representation can be quite efficient, providing solutions to many cla...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
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2013
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/99223 http://hdl.handle.net/10220/17209 |
| _version_ | 1811687099563245568 |
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| author | Blachnik, Marcin Kordos, Miroslaw Duch, Włodzisław |
| author2 | School of Computer Engineering |
| author_facet | School of Computer Engineering Blachnik, Marcin Kordos, Miroslaw Duch, Włodzisław |
| author_sort | Blachnik, Marcin |
| collection | NTU |
| description | Complex neural and machine learning algorithms usually lack comprehensibility. Combination of sequential covering with prototypes based on threshold neurons leads to a prototype-threshold based rule system. This kind of knowledge representation can be quite efficient, providing solutions to many classification problems with a single rule. |
| first_indexed | 2024-10-01T05:10:56Z |
| format | Conference Paper |
| id | ntu-10356/99223 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:10:56Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/992232020-05-28T07:17:41Z Extraction of prototype-based threshold rules using neural training procedure Blachnik, Marcin Kordos, Miroslaw Duch, Włodzisław School of Computer Engineering International Conference on Artificial Neural Networks (22nd : 2012 : Lausanne, Switzerland) DRNTU::Engineering::Computer science and engineering Complex neural and machine learning algorithms usually lack comprehensibility. Combination of sequential covering with prototypes based on threshold neurons leads to a prototype-threshold based rule system. This kind of knowledge representation can be quite efficient, providing solutions to many classification problems with a single rule. 2013-11-01T02:59:45Z 2019-12-06T20:04:50Z 2013-11-01T02:59:45Z 2019-12-06T20:04:50Z 2012 2012 Conference Paper Blachnik, M., Kordos, M., & Duch, W. (2012). Extraction of prototype-based threshold rules using neural training procedure. 22nd International Conference on Artificial Neural Networks, ICANN 2012, pp.255-262. https://hdl.handle.net/10356/99223 http://hdl.handle.net/10220/17209 10.1007/978-3-642-33266-1_32 en |
| spellingShingle | DRNTU::Engineering::Computer science and engineering Blachnik, Marcin Kordos, Miroslaw Duch, Włodzisław Extraction of prototype-based threshold rules using neural training procedure |
| title | Extraction of prototype-based threshold rules using neural training procedure |
| title_full | Extraction of prototype-based threshold rules using neural training procedure |
| title_fullStr | Extraction of prototype-based threshold rules using neural training procedure |
| title_full_unstemmed | Extraction of prototype-based threshold rules using neural training procedure |
| title_short | Extraction of prototype-based threshold rules using neural training procedure |
| title_sort | extraction of prototype based threshold rules using neural training procedure |
| topic | DRNTU::Engineering::Computer science and engineering |
| url | https://hdl.handle.net/10356/99223 http://hdl.handle.net/10220/17209 |
| work_keys_str_mv | AT blachnikmarcin extractionofprototypebasedthresholdrulesusingneuraltrainingprocedure AT kordosmiroslaw extractionofprototypebasedthresholdrulesusingneuraltrainingprocedure AT duchwłodzisław extractionofprototypebasedthresholdrulesusingneuraltrainingprocedure |