MetOffice / MetOffice/ennuf

Add a random forest ennuf model

Open
#4 0 comments 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

enhancement
Dominant language
Python
Stars
4
Forks
4
PR merge metrics
No merged PRs in 30d

Description

Requires completion of #2 first.

The existing ennuf model is really only a neural network model.

An additional model class should be created in a similar manner, representing random forests.

Afterwards, this will then require new translation functions that construct instances of this class, given a random forest instance made using an external library (e.g. sklearn) (should probably be a second ticket)

Contributor guide

No contributing guide indexed for this repository

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 reviewing issue #2 and the existing ennuf neural network model to understand the expected model-class structure. The work is complete when a comparable model class represents random forests; translation functions for external-library instances are explicitly deferred to a separate ticket.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
machine-learning
Issue type
Feature
Difficulty
3/5
Estimated time
1-2 days
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
45/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.