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| author | Douglas Rumbaugh <dbr4@psu.edu> | 2023-07-25 11:17:36 -0400 |
|---|---|---|
| committer | Douglas Rumbaugh <dbr4@psu.edu> | 2023-07-25 11:17:36 -0400 |
| commit | 37434f5baf632e839dc14b3c7d8745287cb9368a (patch) | |
| tree | 4b9a77c25b734872a1b815cc7c0bad6258784601 /external/m-tree | |
| parent | 9e869d32344d5bd8ee703a0733d80d48d458217c (diff) | |
| download | dynamic-extension-37434f5baf632e839dc14b3c7d8745287cb9368a.tar.gz | |
Benchmarks: mtree and vptree benchmark updates
Note: cosine similarity doesn't seem to work for VPTree--I don't think
that it is actually a metric, upon further research. At the very least I
can't find anyone claiming it is, and I've found several people claiming
it isn't. On testing with the Word2Vec data, Euclidean distance works
insofar as the M-Tree and VPTree return the same KNN results for test
queries, whereas Cosine Similarity does not work.
Diffstat (limited to 'external/m-tree')
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