ce-classification
CommunityCalibrated explanations for classification outcomes.
AuthorMoffran
Version1.0.0
Installs0
System Documentation
What problem does it solve?
CE classification provides calibrated probability bounds using Venn-Abers calibration for binary and multiclass semantics to produce reliable explanations.
Core Features & Use Cases
- Explains the predicted class by returning calibrated probabilities and class-specific explanations.
- Supports explaining all classes when multi_labels_enabled is true for contrastive analysis.
- Suitable for pipelines requiring robust uncertainty estimates and interpretable decisions.
Quick Start
Fit your classifier, calibrate its outputs, and generate a fact-based explanation for the model’s predicted class.
Dependency Matrix
Required Modules
None requiredComponents
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: ce-classification Download link: https://github.com/Moffran/calibrated_explanations/archive/main.zip#ce-classification Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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