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Performance metric for multi-class classification
Hi all I've just trained a multi-class classification model with random forest. I have split train-test sets. Apart from Area Under Curve (AUC), what other performance metrics can I use to diagnose/improve the model (?) There are 24 levels for my target variable, I don't think confusion matrix is a good measure (?) Thanks
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Have you tried this :
https://sebastianraschka.com/faq/docs/multiclass-metric.html
This is the first result when you google your subject.