Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Paweł Teisseyre"'
Publikováno v:
Genes, Vol 13, Iss 1, p 121 (2022)
The idea of forensic DNA intelligence is to extract from genomic data any information that can help guide the investigation. The clues to the externally visible phenotype are of particular practical importance. The high heritability of the physical p
Externí odkaz:
https://doaj.org/article/796ec92f914344aca722f514e1c74f76
Publikováno v:
Pattern Recognition. 141:109605
Publikováno v:
Modeling Decisions for Artificial Intelligence ISBN: 9783031334979
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a08835d501b00a6bcfefd4476699d59d
https://doi.org/10.1007/978-3-031-33498-6_8
https://doi.org/10.1007/978-3-031-33498-6_8
Publikováno v:
Advances in Data Analysis and Classification. 15:1039-1068
In the paper, we revisit the problem of class prior probability estimation with positive and unlabelled data gathered in a single-sample scenario. The task is important as it is known that in positive unlabelled setting, a classifier can be successfu
Autor:
Paweł Teisseyre, Jaesung Lee
Publikováno v:
Expert Systems with Applications. 216:119436
Publikováno v:
Pattern Recognition. 86:290-319
Feature selection is one of the trending challenges in multi-label classification. In recent years a lot of methods have been proposed. However the existing approaches assume that all the features have the same cost. This assumption may be inappropri
Autor:
Anna Woźniak, Magdalena Zubańska, Ewelina Pośpiech, Agata Jarosz, Magdalena Kukla-Bartoszek, Michał Boroń, Tomasz Grzybowski, Jan Mielniczuk, Piotr Zieliński, Michał Dąbrowski, Joanna Karłowska-Pik, Rafał Płoski, Magdalena Spólnicka, Paweł Teisseyre, Wojciech Branicki
Publikováno v:
International Journal of Legal Medicine
Increasing understanding of human genome variability allows for better use of the predictive potential of DNA. An obvious direct application is the prediction of the physical phenotypes. Significant success has been achieved, especially in predicting
Autor:
Jan Mielniczuk, Paweł Teisseyre
Publikováno v:
Computational Science – ICCS 2021 ISBN: 9783030779795
ICCS (6)
ICCS (6)
We consider a problem of detecting the conditional dependence between multiple discrete variables. This is a generalization of well-known and widely studied problem of testing the conditional independence between two variables given a third one. The
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::301abba7a89677fae692dd25a8da132c
https://doi.org/10.1007/978-3-030-77980-1_51
https://doi.org/10.1007/978-3-030-77980-1_51
Autor:
Tomasz Klonecki, Paweł Teisseyre
Publikováno v:
Computational Science – ICCS 2021 ISBN: 9783030779634
ICCS (2)
ICCS (2)
Feature selection in supervised classification is a crucial task in many biomedical applications. Most of the existing approaches assume that all features have the same cost. However, in many medical applications, this assumption may be inappropriate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1105f0d90c02046dcf5db3f3954f5717
https://doi.org/10.1007/978-3-030-77964-1_37
https://doi.org/10.1007/978-3-030-77964-1_37
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030504229
ICCS (4)
ICCS (4)
In the paper we revisit the problem of fitting logistic regression to positive and unlabelled data. There are two key contributions. First, a new light is shed on the properties of frequently used naive method (in which unlabelled examples are treate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9c78732d2700bf764e307b1ffd301ceb
https://doi.org/10.1007/978-3-030-50423-6_1
https://doi.org/10.1007/978-3-030-50423-6_1