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Measuring Hash & Fingerprint Quality #3

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Expand Up @@ -302,6 +302,11 @@ Adjusting all implementation to the same tokenization scheme, one my experience
| | 86.80% collisions | 93.21% collisions |
| | 0.9992 entropy | 0.9967 entropy |

The trickiest part, however, is analyzing the retrieval quality of those fingerprints and comparing them to other approaches.
So, how many bits per fingerprint are needed to achieve a specific recall rate for a given dataset?
Or, how does the average Levenshtein distance among the top-k nearest neighbors change with the fingerprint size?
It must clearly decrease, but how fast, and how does that compare to ground truth?

## Replicating the Results

### Replicating the Results in Rust 🦀
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