OneVsAllClassifier fits two trainers for binary classification task

### System information

- **OS version/distro**:
- **.NET Version (eg., dotnet --info)**:

### Issue

- **What did you do?**
- **What happened?**
- **What did you expect?**
I expected OneVsAll to identify there are only two classes and train a single learner.

### Source code / logs

Internally the OneVersusAllTrainer will always instantiate as many binary classifiers as the number of classes. This is inefficient for binary classification, as just a single trainer is needed. I understand that I can just use an out of the box binary classification for this, but it will simplify the usage.