[tobltobs]

How do you get the data for training how a break-in looks like?

[marsRoverDev]

Couldn't you just train it on genuine visitors and then use the probability of it being a genuine visitor to determine whether it is a break in?

[kmmlng]

I imagine only training on genuine visitors would be tricky with any traditional classification approach. Even having a 90/10% split of positive/negative training data is difficult since a lot of classifiers will just degrade to a majority vote.

Maybe a Restricted Boltzmann Machine or something similar?

[network_ops]

I'm guessing this would also use data for time of day, and if anyone is at home

[headcanon]

possibly some kind of anomaly detection, but I'm not sure how you would model the data.