CoreML on-device model training with tabular data

Question

I'm trying to build an app that makes suggestions (distinct classes) based on a table with 4 features: latitude, longitude, time and weekday.

The training data of my app is 100% personal, so it doesn't really make sense to pre-train the model. I wanna be able to train on device. I know CoreML 3 supports updating for neural networks and kNN classifiers, but does this really help me with my tabular data?

Other tabular classifiers like boasted tree, random forest... can't be trained on device unfortunately. Are there alternatives to CoreML for on device training of those simpler machine learning algorithms? Or can CoreML somehow already do what I want.

Unfortunately I'm not really an expert in neural networks.

Answer 1

Just because Core ML doesn't provide something, doesn't mean it's impossible. :-) You can use existing libraries or implement the algorithm by yourself.

If you're looking to build a logistic regression classifier, this is fairly easy to implement by hand. (You can even use a neural network with a single layer for this and still use Core ML.)