Negative sampling features

Open
#773 2 comments 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

Assessment

Difficulty
5/5
Estimated time
Over a week
Newbie friendliness
25/100
Issue type
Feature
Clarity
Mostly clear
Activity status
Stale
Tech stack
python
Domain
machine-learning

Research direction

Start by reviewing the NVT/Merlin dataloaders and the related requirements in issue #356. The checklist defines four negative-sampling variants to cover; done means the requested popularity-biased and uniform strategies, including recent-item behavior, are integrated into the dataloaders.

Written by the indexing model from the issue text.

Description

Sampling

We'd like to integrate several varieties of negative sampling into the NVT/Merlin dataloaders:

  • Popularity biased negatives from in-batch examples
  • Uniform negatives from all items
  • Uniform negatives from recent items (from #356)
  • Popular items based on recent interactions (from #356)
Dominant language
Python
Stars
1.2k
Forks
149
No merged PRs in 30d

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

More from NVIDIA-Merlin/NVTabular

All issues in NVIDIA-Merlin/NVTabular

Similar issues

More Python issues

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.