Active learning for electrodermal activity classification
To filter noise or detect features within physiological signals, it is often effective to encode expert knowledge into a model such as a machine learning classifier. However, training such a model can require much effort on the part of the researcher; this often takes the form of manually labeling p...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Institute of Electrical and Electronics Engineers (IEEE)
2017
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| Online Access: | http://hdl.handle.net/1721.1/109392 https://orcid.org/0000-0002-8413-9469 https://orcid.org/0000-0003-4133-9230 https://orcid.org/0000-0002-9857-0188 https://orcid.org/0000-0002-5661-0022 |