erdogant/KNRscore
KNRScore is a Python package for computing K-Nearest-Rank Similarity, a metric that quantifies local structural similarity between two maps or embeddings.
When you're comparing two different data visualizations, like t-SNE plots or PCA embeddings, KNRscore helps you quantify how similar the local neighborhoods of data points are between them. It takes your two visualizations (or 'maps') as input and outputs a score from 0 to 1, indicating their structural similarity. This tool is useful for data scientists, machine learning engineers, and researchers who create and interpret data embeddings to understand their data better.
No commits in the last 6 months. Available on PyPI.
Use this if you need to objectively compare and score the local structural similarity between different data embeddings or visualizations, like checking if two different dimensionality reduction methods preserve similar relationships between data points.
Not ideal if you are looking for a tool to generate data embeddings or visualizations from raw data; this tool focuses solely on comparing existing ones.
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Python
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Last pushed
Aug 30, 2025
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Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/erdogant/KNRscore"
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