The importance of data quantity in machine learning: how small is too small?
Beverly Yang, Andrew Tsai, Amichai Mitelman, Rita Tsai, Davide Elmo
Dans les comptes rendus d’articles de la conférence: GeoSaskatoon 2023: 76th Canadian Geotechnical ConferenceSession: Innovative Geotechnical
Please include this code when submitting a data update: GEO2023_149
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Citer cet article:
Yang, Beverly, Tsai, Andrew, Mitelman, Amichai, Tsai, Rita, Elmo, Davide (2023) The importance of data quantity in machine learning: how small is too small? in GEO2023. Ottawa, Ontario: Canadian Geotechnical Society.
@inproceedings{Yang_GEO2023_149,
author = {{Yang, Beverly}, {Tsai, Andrew}, {Mitelman, Amichai}, {Tsai, Rita}, {Elmo, Davide}}
title = {The importance of data quantity in machine learning: how small is too small? }
booktitle = {Proceedings of the 76th Canadian Geotechnical Conference}
year = {2023}
organization = {The Canadian Geotechnical Society},
address = {Ottawa, Canada} }
title = {The importance of data quantity in machine learning: how small is too small? }
booktitle = {Proceedings of the 76th Canadian Geotechnical Conference}
year = {2023}
organization = {The Canadian Geotechnical Society},
address = {Ottawa, Canada} }