The process of recording local fields potentials can be influenced by many internal and
external sources of electrical noise. To successfully use these recordings, noise must be
removed, for which an automatic detection tool is needed to speed up the reviewing
process. This research aims to develop an interpretable model, and among the many
machine learning models, decision trees stand out due to the innate ability to allow insight
into the classification criteria. As they require extracted features instead of the raw signal to …

The process of recording local fields potentials can be influenced by many internal and
external sources of electrical noise. To successfully use these recordings, noise must be
removed, for which an automatic detection tool is needed to speed up the reviewing
process. This research aims to develop an interpretable model, and among the many
machine learning models, decision trees stand out due to the innate ability to allow insight
into the classification criteria. As they require extracted features instead of the raw signal to …