Zobrazeno 1 - 10
of 37
pro vyhledávání: '"Andreas Henelius"'
Publikováno v:
Frontiers in Computer Science, Vol 5 (2023)
In recent years the use of complex machine learning has increased drastically. These complex black box models trade interpretability for accuracy. The lack of interpretability is troubling for, e.g., socially sensitive, safety-critical, or knowledge
Externí odkaz:
https://doaj.org/article/c6bd5b0a83b648c5937531ce1930b466
Autor:
Andreas Henelius, Jari Torniainen
Publikováno v:
SoftwareX, Vol 7, Iss , Pp 156-161 (2018)
Data streams are pervasive but implementing online analysis of streaming data is often nontrivial as data streams can have different, domain-specific formats. Regardless of the stream, the analysis task is essentially the same: features are extracted
Externí odkaz:
https://doaj.org/article/5db3771746c943df983df997e1503b24
Autor:
Kiti Müller, Ilari Rautalin, Lauri Ahonen, Anne Arola, Andreas Henelius, Hanna Jokinen, Jussi Korpela, Miikka Korja, Nicolas Martinez-Majander, Aaro Mustonen, Teemu Paajanen, Satu Pakarinen, Kati Pettersson, Jukka Putaala, Laura Sokka, Tuomas Tikka, Jussi Virkkala
ObjectivesReasons for a patient’s daily problems are often unclear as they are not systematically monitored in daily life. To remedy this, we designed a study protocol combining outpatient laboratory and home measurements. Feasibility of the protoc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::89fa77b27c2b8f362bb2cd8fd562fad1
https://doi.org/10.1101/2023.01.30.23285187
https://doi.org/10.1101/2023.01.30.23285187
Publikováno v:
Data Mining and Knowledge Discovery. 35:726-747
Regression analysis is a standard supervised machine learning method used to model an outcome variable in terms of a set of predictor variables. In most real-world applications the true value of the outcome variable we want to predict is unknown outs
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8c2a4b5d95682e4930c8f3c2f11c7e84
https://doi.org/10.1007/s10618-021-00739-7
https://doi.org/10.1007/s10618-021-00739-7
Real-world datasets are often characterised by outliers; data items that do not follow the same structure as the rest of the data. These outliers might negatively influence modelling of the data. In data analysis it is, therefore, important to consid
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ed56d04519970287c13321c5c1aa28b6
http://hdl.handle.net/10138/342187
http://hdl.handle.net/10138/342187
Publikováno v:
Behaviour & Information Technology. 38:1038-1047
Today's ever-increasing amount of data places new demands on cognitive ergonomics and requires new design ideas to ensure successful human-data interaction. Our aim was to identify the cognitive factors that must be considered when designing systems
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1884267373895ca00de1a4cba860a4b2
https://doi.org/10.1080/0144929x.2019.1657181
https://doi.org/10.1080/0144929x.2019.1657181
Publikováno v:
IEEE Transactions on Visualization and Computer Graphics. :1-1
A fundamental problem in visual data exploration concerns whether observed patterns are true or merely random noise. This problem is especially pertinent in visual analytics, where the user is presented with a barrage of patterns, without any guarant
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7b15dda92d7395f75679ecc66d471abe
https://doi.org/10.1109/tvcg.2022.3175532
https://doi.org/10.1109/tvcg.2022.3175532
Autor:
Antti Tuori, M. Sihvola, Göran Kecklund, Andreas Henelius, Jussi Virkkala, Torbjörn Åkerstedt, Kimmo Ketola, Mikael Sallinen, Marianne Leinikka, Sampsa Puttonen, Mikko Härmä
Publikováno v:
Aerospace Medicine and Human Performance. 89:601-608
Introduction We examined whether long-haul airline pilots without recurrent on-duty sleepiness obtain more prior sleep and use more effective in-flight alertness management strategies than their colleagues with recurrent on-duty sleepiness. Methods T
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ad8150f8c6dd8cc27ba991c094f5ae50
https://doi.org/10.3357/amhp.5092.2018
https://doi.org/10.3357/amhp.5092.2018
Publikováno v:
Discovery Science ISBN: 9783030337773
DS
DS
Real-world datasets are often characterised by outliers, points far from the majority of the points, which might negatively influence modelling of the data. In data analysis it is hence important to use methods that are robust to outliers. In this pa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0d4860963fbb3c82ab6b5693bb4da04e
http://hdl.handle.net/10138/308024
http://hdl.handle.net/10138/308024
Publikováno v:
ECCE
Today's ever-increasing amount of data places new demands on cognitive ergonomics and requires new design ideas to ensure successful human–data interaction. Our aim is to identify the cognitive factors that require attention when designing systems
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ada824b62010d64e4d0422844196c072
https://doi.org/10.1145/3335082.3335112
https://doi.org/10.1145/3335082.3335112