Accenture / Accenture/AmpliGraph
Can we pass custom trained embedding as entity and then train the model?
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- Python
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Description
Hi, we are working on a link prediction task using ampligraph, the triple basically looks like,
protein_sequence, i.e KFLEACD (subject) ---> positive(predicate) ---> assay_1(object)
we already have a better representation of the protein sequence stored as embedding, is it possible to pass those embedding directly as an entity like,
protein_embedding(subject) ---> positive(predicate) ---> assay_1(object)
Please clarify, thanks in advance.
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Research direction
No files, tests, or entry points are named. Start by locating AmpliGraph’s entity-representation and model-training APIs, then determine how externally supplied protein embeddings would participate in link-prediction training and what validation would confirm support.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100