As mentioned earlier, we will now create a multi-class classification application, categorizing email into one of three categories:
- Orders
- Spam
- Friend
Flushing out this example for a production application would more than likely include significantly more categories in addition to more features. However, this is a good starting point to demonstrate a multi-class classification use case.
As with other examples, the complete project code, sample dataset, and project files can be downloaded here: https://github.com/PacktPublishing/Hands-On-Machine-Learning-With-ML.NET/tree/master/chapter04-multiclass.
Diving into the trainer
As previously mentioned, for this multi-class classification application we will be using the SdcaMaximumEntropy trainer.
The SdcaMaximumEntropy class, as the name implies, is based on the SDCA we deep dove into in Chapter 3, Regression Model, and uses empirical risk minimization, which optimizes based on the training...
