| Comparison of feature ranking methods based on information entropy W Duch, T Wieczorek, J Biesiada, M Blachnik 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No …, 2004 | 124 | 2004 |
| Do we need whatever more than k-NN? M Kordos, M Blachnik, D Strzempa Artificial Intelligence and Soft Computing: 10th International Conference …, 2010 | 48 | 2010 |
| Fusion of instance selection methods in regression tasks Á Arnaiz-González, M Blachnik, M Kordos, C García-Osorio Information Fusion 30, 69-79, 2016 | 47 | 2016 |
| Instance selection with neural networks for regression problems M Kordos, M Blachnik Artificial Neural Networks and Machine Learning–ICANN 2012: 22nd …, 2012 | 41 | 2012 |
| Ensembles of instance selection methods based on feature subset M Blachnik Procedia Computer Science 35, 388-396, 2014 | 36 | 2014 |
| Fuzzy rule-based systems derived from similarity to prototypes W Duch, M Blachnik International Conference on Neural Information Processing, 912-917, 2004 | 36 | 2004 |
| Optimization of warehouse operations with genetic algorithms M Kordos, J Boryczko, M Blachnik, S Golak Applied Sciences 10 (14), 4817, 2020 | 35 | 2020 |
| LVQ algorithm with instance weighting for generation of prototype-based rules M Blachnik, W Duch Neural Networks 24 (8), 824-830, 2011 | 34 | 2011 |
| Fuzzy clustering decomposition of genetic algorithm-based instance selection for regression problems M Kordos, M Blachnik, R Scherer Information Sciences 587, 23-40, 2022 | 28 | 2022 |
| Infosel++: Information Based Feature Selection C++ Library A Kachel, J Biesiada, M Blachnik, W Duch Artificial Intelligence and Soft Computing: 10th International Conference …, 2010 | 24 | 2010 |
| Bagging of instance selection algorithms M Blachnik, M Kordos International Conference on Artificial Intelligence and Soft Computing, 40-51, 2014 | 21 | 2014 |
| Comparison of various feature selection methods in application to prototype best rules M Blachnik Computer Recognition Systems 3, 257-264, 2009 | 21 | 2009 |
| Image classification by histogram features created with learning vector quantization M Blachnik, J Laaksonen International Conference on Artificial Neural Networks, 827-836, 2008 | 21 | 2008 |
| Building a model for time reduction of steel scrap meltdown in the electric arc furnace (EAF): General strategy with a comparison of feature selection methods T Wieczorek, M Blachnik, K Ma̧czka Artificial Intelligence and Soft Computing–ICAISC 2008: 9th International …, 2008 | 20 | 2008 |
| Ensembles of instance selection methods: A comparative study M Blachnik International Journal of Applied Mathematics and Computer Science 29 (1), 2019 | 19 | 2019 |
| Comparison of instance selection and construction methods with various classifiers M Blachnik, M Kordos Applied Sciences 10 (11), 3933, 2020 | 18 | 2020 |
| Instance selection for classifier performance estimation in meta learning M Blachnik Entropy 19 (11), 583, 2017 | 18 | 2017 |
| Instance selection in logical rule extraction for regression problems M Kordos, S Białka, M Blachnik Artificial Intelligence and Soft Computing: 12th International Conference …, 2013 | 18 | 2013 |
| Predicting presence of amphibian species using features obtained from gis and satellite images M Blachnik, M Sołtysiak, D Dąbrowska ISPRS International Journal of Geo-Information 8 (3), 123, 2019 | 17 | 2019 |
| Feature Selection for Supervised Classification: A Kolmogorov-Smirnov Class Correlation-Based Filter M Blachnik, W Duch, A Kachel, J Biesiada AIMeth, Symposium On Methods Of Artificial Intelligence. Gliwice, Poland (10 …, 2009 | 17 | 2009 |
Miroslaw KordosUniversity of Bielsko-Biala在 ath.bielsko.pl 的电子邮件经过验证
