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Audio Classification

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NDStein commited on 12 days ago

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@@ -170,7 +170,7 @@ print(f"Highest specificity achievable with sensitivity >= 80% and 35% indetermi
 sn_eq_sp = issa.sn_eq_sp_graph()
 ```
-### Optimal Tuning for Multiclass Tasks
 The depression and anxiety models were each trained with ordinal regression to predict a scalar score monotonically correlated with the underlying PHQ-9 and GAD-7 questionnaire ground truth sums. As such there are efficient dynamic programming algorithms to select optimal thresholds for multi-class numeric labels under a variety of decision criteria.
 ```

 sn_eq_sp = issa.sn_eq_sp_graph()
 ```
+### Optimal Tuning for Multi-class Tasks
 The depression and anxiety models were each trained with ordinal regression to predict a scalar score monotonically correlated with the underlying PHQ-9 and GAD-7 questionnaire ground truth sums. As such there are efficient dynamic programming algorithms to select optimal thresholds for multi-class numeric labels under a variety of decision criteria.
 ```