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On measuring confounding bias in mixed multidimensional data : case of coerced multiple linear regression adjustment

author
Arakkal Peious, Sijo
Kaushik, Minakshi
Shah, Syed Attique
Sharma, Rahul
Suran, Shweta
Draheim, Dirk
statement of authorship
Sijo Arakkal Peious, Minakshi Kaushik, Syed Attique Shah, Rahul Sharma, Shweta Suran and Dirk Draheim
source
ICT for Intelligent Systems : proceedings of ICTIS 2024. Vol. 6
location of publication
Singapore
publisher
Springer
year of publication
2024
pages
p. 329–342
series
Lecture notes in networks and systems ; 1112
conference name, date
ICTIS’2024 – the 8th International Conference on ICT for Intelligent Systems
conference location
Ahmedabad, India
url
https://doi.org/10.1007/978-981-97-6684-0_27
subject term
andmed
mõõtmine
mitmemõõtmeline analüüs
tark linn
Scopus
Conference proceedings at Scopus
Article at Scopus
quartile
Q4
category (general)
Computer science
Engineering
category (sub)
Computer science. Signal processing
Engineering. Control and systems engineering
Computer science. Computer networks and communications
keyword
association rule mining
confounder adjustment
confounding
decision support systems
environmental sciences
linear regression
smart cities
ISSN
2367-3370
ISBN
978-981-97-6683-3
978-981-97-6684-0
notes
Bibliogr.: 32 ref
scientific publication
teaduspublikatsioon
classifier
3.1
TalTech department
tarkvarateaduse instituut
language
inglise
Related publications
Arakkal Peious, S., Kaushik, M., Shah, S.A., Sharma, R., Suran, S., Draheim, D. On measuring confounding bias in mixed multidimensional data : case of coerced multiple linear regression adjustment // ICT for Intelligent Systems : proceedings of ICTIS 2024. Vol. 6. Singapore : Springer, 2024. p. 329–342. (Lecture notes in networks and systems ; 1112). https://doi.org/10.1007/978-981-97-6684-0_27