Zobrazeno 1 - 10
of 32
pro vyhledávání: '"Nikos Fazakis"'
Autor:
Nikos Fazakis, Otilia Kocsis, Elias Dritsas, Sotiris Alexiou, Nikos Fakotakis, Konstantinos Moustakas
Publikováno v:
IEEE Access, Vol 9, Pp 103737-103757 (2021)
A steady rise has been observed in the percentage of elderly people who want and are still able to contribute to society. Therefore, early retirement or exit from the labour market, due to health-related issues, poses a significant problem. Nowadays,
Externí odkaz:
https://doaj.org/article/7b8950602f2d408eaca8e25d2edb1dd9
Autor:
Christos K. Aridas, Stamatis Karlos, Vasileios G. Kanas, Nikos Fazakis, Sotiris B. Kotsiantis
Publikováno v:
IEEE Access, Vol 8, Pp 2122-2133 (2020)
In many real world classification tasks, all data classes are not represented equally. This problem, known also as the curse of class imbalanced in data sets, has a potential impact in the training procedure of a classifier by learning a model that w
Externí odkaz:
https://doaj.org/article/4602df0ef4fe4c779b12ca0832dfa5e6
Publikováno v:
IEEE Access, Vol 8, Pp 90555-90569 (2020)
In many real-world applications scientists are often confronted with the problem of incomplete datasets due to several reasons. The direct analysis of datasets with missing values in attributes inevitably results in inaccurate learning models and err
Externí odkaz:
https://doaj.org/article/ed03ef9dd3df4bbe8f5026564b67e620
Publikováno v:
Entropy, Vol 21, Iss 10, p 988 (2019)
One of the major aspects affecting the performance of the classification algorithms is the amount of labeled data which is available during the training phase. It is widely accepted that the labeling procedure of vast amounts of data is both expensiv
Externí odkaz:
https://doaj.org/article/99e34cf1837d4486a6716c86f2c76618
Publikováno v:
Applied Computational Intelligence and Soft Computing, Vol 2016 (2016)
Classification is one of the most important tasks of data mining techniques, which have been adopted by several modern applications. The shortage of enough labeled data in the majority of these applications has shifted the interest towards using semi
Externí odkaz:
https://doaj.org/article/5bb745ad138348fe94023a8e538d28b2
Autor:
Stamatis Karlos, Sotiris Kotsiantis, Nikos Fazakis, Kyriakos N. Sgarbas, Georgios Kostopoulos
Publikováno v:
Intelligent Data Analysis. 24:607-623
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0b710e5534ac43e17571a41409ad615e
https://doi.org/10.3233/ida-194608
https://doi.org/10.3233/ida-194608
Publikováno v:
IEEE Access, Vol 8, Pp 90555-90569 (2020)
In many real-world applications scientists are often confronted with the problem of incomplete datasets due to several reasons. The direct analysis of datasets with missing values in attributes inevitably results in inaccurate learning models and err
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5a964bb817a78e723148bf937b071e26
https://doi.org/10.1109/access.2020.2994033
https://doi.org/10.1109/access.2020.2994033
Publikováno v:
IEEE Access, Vol 8, Pp 2122-2133 (2020)
In many real world classification tasks, all data classes are not represented equally. This problem, known also as the curse of class imbalanced in data sets, has a potential impact in the training procedure of a classifier by learning a model that w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::43a7d47a1bc95a19da92fc921b1123a1
https://ieeexplore.ieee.org/document/8939418/
https://ieeexplore.ieee.org/document/8939418/
Publikováno v:
Pattern Recognition Letters. 125:758-765
The production of vast amounts of data has increased the necessity of applying Machine Learning (ML) and Pattern Recognition (PR) methods that could perform accurate predictive performance without demanding much human effort for collecting and prepar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8a9fbe99cea37e4039fd60648424698c
https://doi.org/10.1016/j.patrec.2019.07.022
https://doi.org/10.1016/j.patrec.2019.07.022
Publikováno v:
IJCCI
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1c33dfa9eadd6d22fa7939317d138533
https://doi.org/10.5220/0010727200003063
https://doi.org/10.5220/0010727200003063