Clarify that multi-class example isn't expected to yield predictions

Open Beginner friendly
#774 0 comments 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

Assessment

Difficulty
2/5
Estimated time
1-3 hours
Newbie friendliness
68/100
Issue type
Documentation
Clarity
Clearly specified
Activity status
Stale
Tech stack
python
Domain
documentation, machine-learning

Research direction

Open the multi-class example at advanced_features/multi_species.html and review the section describing training for one epoch. Clarify that the single-image, one-epoch example is not expected to produce predictions, and include the approximate training context mentioned in the issue. Done means the documentation sets expectations clearly for the example’s zero-tree output.

Written by the indexing model from the issue text.

Description

Our current multi-class example in the docs trains on a single image for 1 epoch. It unsurprisingly doesn't learn anything and therefore predicts zero trees. This is confusing - see #773. We should clarify this in the docs and perhaps provide an idea of how many epochs the example would have to be trained for to show any results (~500 and then it only predicts dead trees).

Dominant language
Python
Stars
774
Forks
265
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 weecology/DeepForest

All issues in weecology/DeepForest

Similar issues

More Python issues

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.