SciML / SciML/EasyModelAnalysis.jl

Super Ensemble Model calibration

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Dominant language
Julia
Stars
87
Forks
14
Avg merge
21h 12m
Merged PRs (30d)
19

Description

Take all of the models and the skill weights as parameters and fit the whole model together.

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

The issue names no files, tests, or entry points. First map how models and skill weights are currently represented and fitted in the package, then define the expected joint-calibration behavior and tests that would show the ensemble is fitted correctly.

Written by the indexing model from the issue text.

Assessment

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

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