Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Agnieszka Duraj"'
Autor:
Agnieszka Duraj, Daniel Duczymiński
Publikováno v:
Entropy, Vol 25, Iss 8, p 1121 (2023)
The present article is devoted to outlier detection in phases of human movement. The aim was to find the most efficient machine learning method to detect abnormal segments inside physical activities in which there is a probability of origin from othe
Externí odkaz:
https://doaj.org/article/393f35cc0718434cbba8f11c50518723
Publikováno v:
Applied Sciences, Vol 11, Iss 16, p 7434 (2021)
Datasets frequently contain uncertain data that, if not interpreted with care, may affect information analysis negatively. Such rare, strange, or imperfect data, here called “outliers” or “exceptions” can be ignored in further processing or,
Externí odkaz:
https://doaj.org/article/114eb32d878540c79d8df480dee353d7
Autor:
Agnieszka Duraj
Publikováno v:
PRZEGLĄD ELEKTROTECHNICZNY. 1:239-242
Autor:
Agnieszka Duraj
Publikováno v:
PRZEGLĄD ELEKTROTECHNICZNY. 1:207-210
Autor:
Agnieszka Duraj, Piotr Szczepaniak
Publikováno v:
Procedia Computer Science. 207:1953-1958
Publikováno v:
Procedia Computer Science. 207:1212-1221
Autor:
Agnieszka Duraj, Adam Niewiadomski
Publikováno v:
International Journal of Fuzzy Systems. 23:878-889
Uncertainty appearing in datasets (stochastic, linguistic, of measurements, etc.), if not handled properly, may negatively affect information analysis or retrieval procedures. One of possible methods of dealing with uncertain (rare, strange, unexampl
Autor:
Agnieszka Duraj
Publikováno v:
PRZEGLĄD ELEKTROTECHNICZNY. 1:39-42
Autor:
Piotr S. Szczepaniak, Agnieszka Duraj
Publikováno v:
Computational Science – ICCS 2021 ISBN: 9783030779795
ICCS (6)
ICCS (6)
The practice of textual and numerical information processing often involves the need to analyze and test a database for the presence of items that differ substantially from other records. Such items, referred to as outliers, can be successfully detec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8372f795a1d734d46445c4d289ba7c97
https://doi.org/10.1007/978-3-030-77980-1_38
https://doi.org/10.1007/978-3-030-77980-1_38