[sulexk]

Building a smart home security system, so you can be notified when your friends have arrived, or if someone is trying to break into your home. Machine learning is very useful here, as you can train the system to recognise what your friends look like, or what a break-in might look like.

[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.

[LaurensBER]

How do you collect training data for break-ins?

Did you put an add out on craigslists requesting for people to attempt it or do you have some criminal connections?