-
Notifications
You must be signed in to change notification settings - Fork 10
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Dataset similarity #122
base: main
Are you sure you want to change the base?
Dataset similarity #122
Conversation
- Add new class that performs k-nearest neighbor searches using Tanimoto similarity. The implementation uses sparse dot product making the algorithm 2-3x faster than RDKit's BulkTanimotoSimilarity - Add notebook illustrating NearestNeighborsRetrieverTanimoto for dataset similarity analysis, like train/test set comaparison.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
In addition as discussed: Make it an estimator
else: | ||
self.k = k | ||
self.batch_size = batch_size | ||
if n_jobs == -1: |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Maybe use this function instead?
https://github.com/basf/MolPipeline/blob/main/molpipeline/utils/multi_proc.py#L9
Tanimoto similarity. The implementation uses sparse dot product
making the algorithm 2-3x faster than RDKit's BulkTanimotoSimilarity
dataset similarity analysis, like train/test set comaparison.
Also addresses #117