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Wiesław Paja
Wiesław Paja
Assistant Professor of Computer Science, University of Rzeszów
Dirección de correo verificada de ur.edu.pl
Título
Citado por
Citado por
Año
Feature selection for data and pattern recognition: An introduction
U Stańczyk, LC Jain
Feature Selection for Data and Pattern Recognition, 1-7, 2015
1662015
All relevant feature selection methods and applications
WR Rudnicki, M Wrzesień, W Paja
Feature Selection for Data and Pattern Recognition, 11-28, 2015
1092015
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
672019
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
42*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
392022
Advances in feature selection for data and pattern recognition
U Stańczyk, B Zielosko, LC Jain
Springer International Publishing, 2018
342018
Advances in data mining
P Perner
Springer Berlin/Heidelberg., 2002
33*2002
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
262022
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
222018
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
192003
An application of raman spectroscopy in combination with machine learning to determine gastric cancer spectroscopy marker
Z Guleken, P Jakubczyk, W Paja, K Pancerz, A Wosiak, İ Yaylım, ...
Computer Methods and Programs in Biomedicine 234, 107523, 2023
182023
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
182022
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
162022
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
162002
Feature selection methods based on decision rule and tree models
W Paja
Intelligent Decision Technologies 2016: Proceedings of the 8th KES …, 2016
152016
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, 1-7, 2013
152013
Man-machine interactions 2
T Czachórski, S Kozielski, U Stanczyk
Springer Science & Business Media, 2011
15*2011
Melanoma important features selection using random forest approach
W Paja, M Wrzesień
2013 6th International conference on human system interactions (HSI), 415-418, 2013
132013
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
132005
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
112016
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Artículos 1–20