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      Analyze Model Performance (Video)
      • 23 Oct 2024
      • 1 Minute to read
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      Contents

      Analyze Model Performance (Video)

      • Updated on 23 Oct 2024
      • 1 Minute to read
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      Article summary

      This article applies to these versions of LandingLens:

      LandingLensLandingLens on Snowflake
      ✓✓

      LandingLens offers several metrics to help you understand how a model performs. This video explains some of the key metrics and concepts, including confidence score, confidence threshold, precision, recall, True Positives, True Negatives, False Positives, and False Negatives.

      Notes:
      • Confidence thresholds are only applicable to Object Detection and Segmentation projects.
      • For Object Detection, the F1 score combines precision and recall into a single score, creating a unified measure that assesses the model’s effectiveness in minimizing false positives and false negatives. For Classification, the F1, Precision, and Recall scores are identical. This is because Classification models have only two prediction outcomes: "Correct" and "Misclassified".
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