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Application note content performance metric additional reference update

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content/hardware/04.pro/boards/portenta-x8/tutorials/15.edge-ai-docker-container
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`@@ -412,6 +412,8 @@ Once training is complete, the model's accuracy is evaluated using a confusion m`
`412`	`412`	`\| Weighted Average F1 Score \| 0.77 \|`
`413`	`413`	`\| Area Under ROC Curve (AUC) \| 0.86 \|`
`414`	`414`
	`415`	`+*For a detailed explanation of each metric, please refer to the [Edge Impulse concept documentation](https://docs.edgeimpulse.com/docs/concepts/glossary-of-terms).*`
	`416`	`+`
`415`	`417`	`The confusion matrix provides insights into model performance across different categories:`
`416`	`418`
`417`	`419`	- `Anomalous` flow conditions are 100% correctly classified.

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