Intelligent Benchmark Relational Analysis for Heuristic Index Modeling
Project description
IBRAHIM (Intelligent Benchmark Relational Analysis for Heuristic Index Modeling)
A novel machine learning framework for multi-criteria decision analysis and benchmark-based ranking.
📊 Overview
IBRAHIM is an intelligent analytical model that evaluates multiple records based on many variables, determines the highest benchmark, and computes ranking scores. It combines elements of multi-criteria decision analysis (MCDA) with machine learning for robust, automated benchmarking.
Key Features
- Automatic Feature Direction Detection: Determines whether variables should be maximized or minimized
- Intelligent Benchmark Generation: Creates ideal benchmark records based on feature directions
- Flexible Weight Assignment: Supports both automatic (ML-based) and manual weight specification
- 0-100 Scoring Scale: Intuitive, normalized scores for easy interpretation
- New Record Evaluation: Compare any new record against the established benchmark
- Visualization Tools: Built-in plotting for ranking analysis
🚀 Installation
From PyPI (once published)
pip install ibrahim
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