Hi richard,
- operating system: Windows 10
Trying to perform similar thing with different column.
The current event column that Iām trying to use contains scores after event/class change based on the performance.
events = mne.find_events(raw,consecutive=True,initial_event=True,shortest_event = 1)
150 events found
Event IDs: [ 9 11 12 14 ā¦ 83 84 87 88 100]
- The event column only registered values for 200 instances (when the events ended) but EEG have instance up to 30000. Therefore the remaining have no values. And also both are in separate file and have different time stamps.
- Is there any way to perform feature extraction and logistic regression after removing bad stretches without the use of events and epochs.
- How do I round of these events/scores to 10? So we can have 10 variables instead of 40.
Thanks