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confidence-calibration

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Keep calibration diagnostics accurate and clear.

Data & Analytics#ui#analytics#validation#diagnostics#calibration#confidence
AuthorEnesMeyzin98
Version1.0.0
Installs0

System Documentation

What problem does it solve?

Confidence calibration diagnostics ensure that the predicted confidence bands align with realized outcomes, preventing misleading interpretations of model certainty.

Core Features & Use Cases

  • Validate alignment between predicted confidence bands and actual results.
  • Surface calibration quality in analytics dashboards and operator UI.
  • Use Case: extend or inspect calibration logic in app/learning/analytics.py and verify UI calibration surfaces remain descriptive.

Quick Start

Validate the current calibration state by comparing predicted bands to realized outcomes and flag any miscalibration for review.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: confidence-calibration
Download link: https://github.com/EnesMeyzin98/Meridian/archive/main.zip#confidence-calibration

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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