NVIDIA-BioNeMo / NVIDIA-BioNeMo/KERMT
Molecules clustering code (PCA and K-means) for training datasets:
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- Dominant language
- Python
- Stars
- 99
- Forks
- 18
- Avg merge
- 5d 14h
- Merged PRs (30d)
- 1
Description
Could you please add the script/code for PCA and K-means clustering on the training dataset?
From the paper: "For all public datasets, compounds were clustered into five clusters using K-means based on a PCA-reduced 2048-bit Morgan circular fingerprint (radius 2), and one of the clusters is selected as a test set with the remaining four used as a training set."
I just wanted to make sure the process is as reproducible as possible.
Contributor guide
First steps
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Research direction
The issue names no files, tests, or entry points, so first locate the existing training-dataset preparation code and determine how public datasets and fingerprints are represented. Done means providing a reproducible process that creates radius-2, 2048-bit Morgan fingerprints, reduces them with PCA, forms five K-means clusters, and records the selected test cluster and remaining training clusters.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data, machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100