1
$\begingroup$

I have built a kNN model using scikit learn that is able to predict a binary outcome very well. The data itself is quite basic, it is simply a 1-D waveform. When feeding the waveform into the model it predicts. However, I would like the data to be streamed through the model if that makes sense, but I am running into issues how to implement.

My first thought was to use a sliding window, but I don't know if that's the best way to go about things because depending on the speed at which data arrives, what if I have a case where there are two distinct peaks in my waveform that require two separate classifications. In that case, if I make my window small, then there is not enough data to make a proper classification. Any guidance or literature on methods would be great.

New contributor
GK89 is a new contributor to this site. Take care in asking for clarification, commenting, and answering. Check out our Code of Conduct.
$\endgroup$

Your Answer

GK89 is a new contributor. Be nice, and check out our Code of Conduct.

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.