Computationally Efficient Epileptic Seizure Prediction based on Extremely Randomised Trees

Wong, Sheng Fung; Kuhlmann, Levin

Computationally Efficient Epileptic Seizure Prediction based on Extremely Randomised Trees

https://hdl.handle.net/10779/DRO/DU:26343757

conference contribution

posted on 2024-07-21, 23:14 authored by Sheng Fung Wong, Levin Kuhlmann

Computationally Efficient Epileptic Seizure Prediction based on Extremely Randomised Trees

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DOI - Is version of https://doi.org/10.1145/3373017.3373058

Location

Melbourne, Vic.

Open access

No

Language

eng

Publication classification

E1 Full written paper - refereed

Pagination

1-3

Start date

2020-02-04

End date

2020-02-06

Title of proceedings

ACSW 2020 : Proceedings of the 2020 Australasian Computer Science Week Multiconference

Event

Australasian Computer Science Week. Multiconference (2020 : Melbourne, Vic.)

Publisher

Association for Computing Machinery

Place of publication

New York, N.Y.

Publication URL

http://dx.doi.org/10.1145/3373017.3373058

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Keywords

Computer Science Computer Science, Theory & Methods data science Epilepsy epilepsyecosystem.org extremely randomised trees LONG machine learning Science & Technology seizure prediction Technology

Computationally Efficient Epileptic Seizure Prediction based on Extremely Randomised Trees

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Related Materials

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Open access

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