| | --- |
| | title: Entropy Harvester |
| | emoji: 🌍 |
| | colorFrom: red |
| | colorTo: red |
| | sdk: gradio |
| | sdk_version: 5.44.1 |
| | app_file: app.py |
| | pinned: false |
| | license: mit |
| | --- |
| | # Dataset Energy & Entropy Analyzer (Gradio) |
| |
|
| | A lightweight app that analyzes a CSV and reports: |
| | - Global compressibility (gzip ratio) |
| | - Per-column entropy (numeric via quantile-binning; categorical via counts) |
| | - Monotone runs and run-entropy (numeric columns) |
| | - Sortedness fraction (numeric columns) |
| | - 2D Pareto maxima (first two numeric columns) |
| | - kd-partition entropy approximation (first two numeric columns) |
| | - Overall **Harvestable Energy** score (0–1) |
| |
|
| | ## How it relates to "Harvestable Energy" & range-partition entropy |
| | - Lower entropy and higher compressibility imply more exploitable structure → higher harvestable energy. |
| | - kd-entropy approximates how many bits are needed to split spatial data into simple blocks (a proxy for range-partition entropy). |
| | - Run-entropy captures how many monotone runs are present (adaptive sorting lens). |
| | Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference |
| |
|
