How to create a binary svm classifier?

I have 5 sets of data each with 3 runs of eeg signal acquisitions, and I'm to create a classifier that will distinguish between the rest and mental activity in each run. So first ten seconds are mental activity and then rest for 20s. The class labels are given but its just [1 2 1 2 1 2 1 2 1 2 1 2] for class 1 being mental activity and 2 being rest, for all runs and subjects? To use fitcsvm I need the Y labels array but am not sure how to get that

Answer 1

[Walter Roberson]

The Y labels vector is the same as the class labels vector.

[Somaia Ahmadi]

This was given along with the data; does it change after filtering or putting all the training signals into a single matrix?

[Walter Roberson]

Do any of those operations change the column's identification as belonging to mental activity or rest?

[Somaia Ahmadi]

Nope it should still be mental activity or rest, but I'm worried that if I put all the runs from each subjects together in one matrix the class labels won't apply..

[Walter Roberson]

As long as you keep columns separate you will be fine. (Each column is an individual sample.)

Answer 2

[Image Analyst]

Did you try the Classification Learner app, on the Apps tab, and have the wizard export the code for you?

[Somaia Ahmadi]

Yeah I did, but it wasn't able to find the response variable (which I assume is the class label vectors in the cell array containing the signals)