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[FEA] Enable UMAP to build knn graph using NN Descent - #5910
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rapids-bot[bot] merged 55 commits intoJul 31, 2024
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Oh the check is failing because we need the updated implementation of RAFT NN Descent (linked above)...! |
viclafargue
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Jun 3, 2024
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Great work! Just have a few suggestions. Also, it could be great to add this feature to the simplicial set functions. But, we could do that in another PR too.
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Added warning and linked issue for consistency with previous version |
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/ok to test |
divyegala
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Jul 30, 2024
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/merge |
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/merge |
loulankxh
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Oct 14, 2025
Adding distance epilogue to NN Descent. Planning to use them for the following use cases as of now; - Calculating mutual reachability distance for HDBSCAN (possibly for usage with HDBSCAN - [related PR here](NVIDIA/cuml#5939)) - Enabling `L2SqrtExpanded` distance metric, by `sqrt`-ing the current supported metric (`L2Expanded`) of NN Descent in the distance epilogue. (for usage with UMAP - [related PR here](NVIDIA/cuml#5910)) Authors: - Jinsol Park (https://github.com/jinsolp) Approvers: - Tarang Jain (https://github.com/tarang-jain) - Tamas Bela Feher (https://github.com/tfeher) - Divye Gala (https://github.com/divyegala) URL: NVIDIA#2364
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Description
build_algo=nn_descentoption to UMAP.Now user can choose the knn graph build algorithm between
"brute_force_knn"and"nn_descent"Defaults to
"auto", in which case decides to run with brute force knn or nn descent depending on the given dataset size."auto"decides to run withbrute_force_knnif either 1) data has <= 50K rows OR 2) data is sparse. Otherwise decides to run withnn_descent.50K rows roughly chosen based on grid search below. (runtime in ms) - Discussed with Corey
data_on_hostoption (defaults to False) when callingfit()orfit_transform()Note that brute force knn cannot be used with data on host
Running Benchmarks