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[FEA] Implement nan_euclidean distance metric #4783

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ChrisJar opened this issue Jun 23, 2022 · 2 comments
Open

[FEA] Implement nan_euclidean distance metric #4783

ChrisJar opened this issue Jun 23, 2022 · 2 comments
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? - Needs Triage Need team to review and classify feature request New feature or request inactive-30d inactive-90d

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@ChrisJar
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ChrisJar commented Jun 23, 2022 •
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Is your feature request related to a problem? Please describe.
I wish I could use cuML to calculate euclidean distance on data with missing values in the same way sci-kit learn can with nan_euclidean:

Compute the euclidean distance between each pair of samples in X and Y,
where Y=X is assumed if Y=None. When calculating the distance between a
pair of samples, this formulation ignores feature coordinates with a
missing value in either sample and scales up the weight of the remaining
coordinates

Describe the solution you'd like
I'd like a function that calculates euclidean distance on data with missing values like the scikit-learn function: nan_euclidean_distances. I'd also like to be able to use this as a metric for pairwise_distances.
@ChrisJar ChrisJar added ? - Needs Triage Need team to review and classify feature request New feature or request labels Jun 23, 2022
SreekiranprasadV pushed a commit to SreekiranprasadV/cuml that referenced this issue Jul 1, 2022
rapidsai#4783 Added nan_euclidean distance metric to pairwise_distances
89e13a2
SreekiranprasadV pushed a commit to SreekiranprasadV/cuml that referenced this issue Jul 18, 2022
rapidsai#4783 Added nan_euclidean distance metric to pairwise_distances
234b84e
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This issue has been labeled inactive-30d due to no recent activity in the past 30 days. Please close this issue if no further response or action is needed. Otherwise, please respond with a comment indicating any updates or changes to the original issue and/or confirm this issue still needs to be addressed. This issue will be labeled inactive-90d if there is no activity in the next 60 days.

rapids-bot bot pushed a commit that referenced this issue Aug 30, 2022
@SreekiranprasadV
#4783 Added nan_euclidean distance metric to pairwise_distances (#4797)
1e697db 
Added nan_euclidean distance metric to pairwise_distances to calculate euclidean distance on data with missing values.

- Added Test cases for nan_euclidean_distance functions

Time taken to calculate:
#Data Points | Sklearn | Cuml
      10000       402 us     2.54 ms
      100k         23 ms      3.8 ms
      1M            760 ms    16 ms

GPU specifications:
- Tesla T4 15109MiB

CPU specifications:
- 11th gen intel i7, 8 cores, 16 Logical processors, 32 GB Memory
- Sklearn njobs as default

Authors:
  - https://github.com/Sreekiran096

Approvers:
  - Corey J. Nolet (https://github.com/cjnolet)

URL: #4797
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This issue has been labeled inactive-90d due to no recent activity in the past 90 days. Please close this issue if no further response or action is needed. Otherwise, please respond with a comment indicating any updates or changes to the original issue and/or confirm this issue still needs to be addressed.

jakirkham pushed a commit to jakirkham/cuml that referenced this issue Feb 27, 2023
@SreekiranprasadV
rapidsai#4783 Added nan_euclidean distance metric to pairwise_distanc…
d81465d 
…es (rapidsai#4797)

Added nan_euclidean distance metric to pairwise_distances to calculate euclidean distance on data with missing values.

- Added Test cases for nan_euclidean_distance functions

Time taken to calculate:
#Data Points | Sklearn | Cuml
      10000       402 us     2.54 ms
      100k         23 ms      3.8 ms
      1M            760 ms    16 ms

GPU specifications:
- Tesla T4 15109MiB

CPU specifications:
- 11th gen intel i7, 8 cores, 16 Logical processors, 32 GB Memory
- Sklearn njobs as default

Authors:
  - https://github.com/Sreekiran096

Approvers:
  - Corey J. Nolet (https://github.com/cjnolet)

URL: rapidsai#4797
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