A 1-NN preclassifier for fuzzy k-NN rule
A two-stage classification scheme is presented. In the first stage it is decided which of the two rules, 1-NN or fuzzy k-NN, will be used in the second stage. The proposed approach leads to significant acceleration of the learning process as well as the classification phase.
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| container_end_page | 238 vol.4 |
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| container_start_page | 234 |
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| container_volume | 4 |
| creator | Jozwik, A. Chmieleski, L. Cudny, W. Sklodowski, M. |
| description | A two-stage classification scheme is presented. In the first stage it is decided which of the two rules, 1-NN or fuzzy k-NN, will be used in the second stage. The proposed approach leads to significant acceleration of the learning process as well as the classification phase. |
| doi_str_mv | 10.1109/ICPR.1996.547422 |
| format | Conference Proceeding |
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In the first stage it is decided which of the two rules, 1-NN or fuzzy k-NN, will be used in the second stage. The proposed approach leads to significant acceleration of the learning process as well as the classification phase.</abstract><pub>IEEE</pub><doi>10.1109/ICPR.1996.547422</doi></addata></record> |
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| identifier | ISSN: 1051-4651 |
| ispartof | Proceedings of 13th International Conference on Pattern Recognition, 1996, Vol.4, p.234-238 vol.4 |
| issn | 1051-4651 2831-7475 |
| language | eng |
| recordid | cdi_ieee_primary_547422 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Acceleration Biomedical engineering Biomedical measurements Costs Cybernetics Error analysis Image processing Neural networks Pattern recognition Probability |
| title | A 1-NN preclassifier for fuzzy k-NN rule |
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