Feature selection for data and pattern recognition: An introduction U Stańczyk, LC Jain Feature Selection for Data and Pattern Recognition, 1-7, 2015 | 138 | 2015 |
All relevant feature selection methods and applications WR Rudnicki, M Wrzesień, W Paja Feature Selection for Data and Pattern Recognition, 11-28, 2015 | 97 | 2015 |
Advances in Data Mining P Perner, R Goebel New York [etc.], 2011 | 47* | 2011 |
Deep architectures for long-term stock price prediction with a heuristic-based strategy for trading simulations C Stoean, W Paja, R Stoean, A Sandita PloS one 14 (10), e0223593, 2019 | 41 | 2019 |
Intelligent Information Processing and Web Mining: Proceedings of the International IIS: IIPWM ́03 Conference held in Zakopane, Poland, June 2-5, 2003 MA Klopotek, ST Wierzchon, K Trojanowski Springer Science & Business Media, 2013 | 41 | 2013 |
Characterization of Covid-19 infected pregnant women sera using laboratory indexes, vibrational spectroscopy, and machine learning classifications Z Guleken, P Jakubczyk, P Wiesław, P Krzysztof, H Bulut, E Öten, ... Talanta 237, 122916, 2022 | 31 | 2022 |
Advances in feature selection for data and pattern recognition U Stańczyk, B Zielosko, LC Jain Springer International Publishing, 2018 | 26 | 2018 |
Development of novel spectroscopic and machine learning methods for the measurement of periodic changes in COVID-19 antibody level JD Zozan Guleken, YeşimTuyji Tok, Paweł Jakubczyk, Wiesław Paja, Krzysztof ... Measurement 196 (111258), 2022 | 19 | 2022 |
Diagnosing skin melanoma: Current versus future directions ZS Hippe, S Bajcar, P Blajdo, JP Grzymala-Busse, JW Grzymala-Busse, ... TASK Quarterly 7 (2), 289-293, 2003 | 19 | 2003 |
Generational feature elimination and some other ranking feature selection methods W Paja, K Pancerz, P Grochowalski Advances in feature selection for data and pattern recognition, 97-112, 2018 | 16 | 2018 |
Research on Pre-processing and Post-processing of Data in the Process of Creation Quasi-optimal Decision Trees H Zdzislaws, MM Knap, W Paja Intelligence Methods 11, 13-15, 2002 | 16 | 2002 |
Feature selection methods based on decision rule and tree models W Paja Intelligent Decision Technologies 2016: Proceedings of the 8th KES …, 2016 | 14 | 2016 |
Active enhancer positions can be accurately predicted from chromatin marks and collective sequence motif data A Podsiadło, M Wrzesień, W Paja, W Rudnicki, B Wilczyński BMC systems biology 7 (6), 1-7, 2013 | 14 | 2013 |
Man-Machine Interactions 2 T Czachórski, S Kozielski, U Stanczyk Springer Science & Business Media, 2011 | 14 | 2011 |
Infoscience technology: the impact of internet accessible melanoid data on health issues GB JW, H ZS, M Knap, W Paja Data Science Journal 4, 77-81, 2005 | 13 | 2005 |
Feasibility Studies of Quality of Knowledge Mined from Multiple Secondary Sources: I. Implementation of generic operations W Paja, ZS Hippe Intelligent Information Processing and Web Mining: Proceedings of the …, 2005 | 12 | 2005 |
Correlation between endometriomas volume and Raman spectra. Attempting to use Raman spectroscopy in the diagnosis of endometrioma Z Guleken, H Bulut, B Bulut, W Paja, M Parlinska-Wojtan, J Depciuch Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 274, 121119, 2022 | 11 | 2022 |
Identification of polycystic ovary syndrome from blood serum using hormone levels via Raman spectroscopy and multivariate analysis Z Guleken, H Bulut, B Bulut, W Paja, B Orzechowska, M Parlinska-Wojtan, ... Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 273, 121029, 2022 | 11 | 2022 |
Melanoma important features selection using random forest approach W Paja, M Wrzesień 2013 6th International conference on human system interactions (HSI), 415-418, 2013 | 11 | 2013 |
Application of all-relevant feature selection for the failure analysis of parameter-induced simulation crashes in climate models WRR Wiesław Paja, Mariusz Wrzesień, Rafał Niemiec Geoscientific Model Development 9 (3), 1065-1072, 2016 | 10 | 2016 |