ml-evaluation

Community

Assess ML model performance with metrics.

Authorsencersoylu
Version1.0.0
Installs0

System Documentation

What problem does it solve?

Machine learning evaluation metrics to quantify and interpret model performance across classification and regression tasks.

Core Features & Use Cases

  • Compute standard metrics (accuracy, precision, recall, F1, RMSE, MAE, R^2)
  • Generate ROC-AUC, confusion matrices, and calibration plots
  • Use cases: model validation, comparison, and performance reporting across domains

Quick Start

Apply the evaluation module to a trained model and generate a metrics report.

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: ml-evaluation
Download link: https://github.com/sencersoylu/scholar-flow/archive/main.zip#ml-evaluation

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