NVIDIA-Merlin / NVIDIA-Merlin/Merlin

Session-based quick start: Support pointwise prediction tasks

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Dominant language
Python
Stars
907
Forks
129
PR merge metrics
No merged PRs in 30d

Description

  • Support pointwise predictions taking as input sequential and non-sequential features (e.g. for ranking models or cart abandonment).
  • Whether the targets are binary or regression are going to be inferred from the schema.
  • The user needs to choose whether the sequential model is targeted for next-item prediction or for pointwise predictions. The script will not allow both types of predictions in a MTL approach.

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.

Research direction

Start by locating the session-based quick-start script and its sequential-model configuration. Trace how schema information could distinguish binary targets from regression and how the script selects next-item versus pointwise prediction. Done means pointwise prediction supports sequential and non-sequential features without allowing both prediction modes in one MTL setup.

Written by the indexing model from the issue text.

Assessment

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

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