How can I search for observations eligible to be in the training set?

[bouteloua]

@schoenitz

Does that mean if I see a pothos in a pot, identifying it would actually encourage the AI to recognize it correctly?

Yes, see Ken-ichi’s response here:

@kueda

The vision system is trained on captive / cultivated records. However, our automated suggestions are based on vision results and nearby records, and the nearby records part of it is currently only using RG records, so if vision ranks Canary Island Pine highly, it might get knocked down by the legit lodgepole records in the Transverse Ranges.

Patrick tells me we haven’t run our accuracy tests without the RG requirement, so we’ll do that and see if it makes things better or worse.

Sort of tangential, but it’s also worth noting that our policy of assuming that cultivated plant obs don’t need more IDs means that our cultivated plant records (both images and occurences) probably have less-accurate identifications and are thus less useful for either purpose (probably why we put that RG requirement in there to begin with). I’m aware there are many who would prefer that we remove that part of our quality grade assessment, and it might help situations like this… or it might just make even more identifiers give up in the face of endless potted plants.

And huh, I might be wrong about observations needing a community taxon. Now that I’m looking back at vision model update posts, in May 2020 (in comments), Ken-ichi says “observation taxon or a community taxon”, which is a bit concerning as far as cultivated plants goes.

kueda:
[…]
Training data gets divided into three sets:

Training: these are the labeled (i.e. identified) photos the model trains on, and include photos from observations that

• have an observation taxon or a community taxon
• are not flagged
• pass all quality metrics except wild / naturalized (i.e. we include photos from captive obs; note that “quality metrics” are the things you can vote on in the DQA, not aspects of the quality grade like whether or not there’s a date or whether the obs is of a human)
  […]

I guess that validates my concern here:

@bouteloua

Common themes

[…]

• For plants: large amount of planted (casual grade) observations that remain incorrectly identified

(the FAQ says “This has changed over time, but as of the model released in March 2020, taxa included in the training set must have at least 100 observations, at least 50 of which must have a community ID.”)