You do unsupervised learning without labels with a linear regression. Interesting. What would you regress in this case? The problem is the following: you have a point cloud of data (electronic signal from arrays arranged into an irregular pattern). You know the physics that was discovered. You are looking for rare events (one in a billion or less) and you don’t know what they look like.
And you think we did not try linear regressions? This is what we used to do 20 years ago. Then we gained two orders of magnitude in signal-to-background discrimination. And since our data are not even images, off-shelf solutions mostly don’t apply. Try to process40 MHz of incoming collisions (1 MB each) within 100 nsec with a linear regression of point-cloud data. When you are done trying, try to think that maybe (maybe…) life is not as easy as bread&butter. If you succeed, come and knock at CERN’s door. Maybe we will let you in…