Asymmetric Cost Loss Function (False Negative Cost = 0) — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited Asymmetric Cost Loss Function (False Negative Cost = 0) (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Defines a custom loss function in TensorFlow/Keras where predicting 1 as 0 (False Negative) has zero cost, while predicting 0 as 1 (False Positive) has a cost of 1.
Define a custom loss function in TensorFlow/Keras. The loss function must implement the logic where the cost of False Negatives (predicting 1 as 0) is 0. The cost of False Positives (predicting 0 as 1) is 1. Ensure type casting to float32 to avoid type mismatch errors.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.