tao-analyze-changenet-rca
Skill performing root cause analysis on TAO Visual ChangeNet experiments.
About
Performs deep Root Cause Analysis (RCA) on NVIDIA TAO Visual ChangeNet classification experiments with image-evidence-driven investigation. Use when analyzing ChangeNet model failures, investigating poor recall / FAR / PASS-NO_PASS metrics, auditing visual inspection pipeline quality, or running an RCA report for an AOI defect-detection model. Trigger phrases include "RCA on my ChangeNet model", "why is my AOI model failing", "audit ChangeNet predictions", "investigate FAR regressions", "root cause analysis on visual-changenet".
At a glance
- Category
- AI models and MLOps Evals
- Made for
- Developers
- Pricing
- Free
- Access
- No sign-in
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Capabilities
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Provenance
- Discovered
- Relayed by agntcy
- Identifier
- urn:air:outshift.io:agntcy:tao-analyze-changenet-rca
- Catalog host
- outshift.io · via agntcy registry
- Anchor check
- Not anchored
- Last crawled
- seen 5h ago
Discovered through outshift.io's registry, not anchored by StealthStack. We relay the listing as-is; we have not checked that the URN authority matches the publishing host. How trust works →