Q:

ML.NET and Many to many relation

I want to use ML.Net Multi-class classification in my current project that collects error logs from one my company systems.
Point is to add tags to errors and one point in the future train a model to predict and assign tags to incoming logs.
I'm using a model builder and I can't see my table relations, I store all logs in one table, tags in another and all relations in the third one.
|Logs| <-- |LogId|TagId| --> |Tags|

My goal is to classify table with TagId column based on Logs table - is that possible? or do I have to have everything in one table?

A:

Generally speaking, machine learning algorithms are dealing with the fully 'denormalized' and 'prepared' data: every training example is vector of floats ('features'), and one 'ground truth' value.
ML.NET helps with some of the typical pre-processing tasks, like text featurization, one-hot encoding, rescaling/normalization, but it doesn't provide pretty much any 'relational' functionality (no JOINs).
So, you should de-normalize / 'flatten' your data before you pass it to ML.NET.

