I have a balanced dataset for a multiclass classification problem with one high-priority label (this ought to be classified properly at all costs). How do I go about creating a workflow for this problem? What specific feature engineering/selection methods and classifiers should I be considering for this problem?
To be more specific, the data I'm dealing with (including labels) is completely anonymized, so I don't have a clue as to what it actually stands for.
Some approaches I am considering -
- Creating synthetic data points for the priority label through oversampling.
- Creating a highly non-linear model for prediction as accuracy is very important.
Any help is much appreciated!