Machine Learning of Parameter Groups and the Impossibility of Universal Aesthetic Prediction

Posted: October 20, 2020 at 10:52 am

Since I’ve been having trouble with generalizing classifier results (where the model achieves tolerable accuracy on training, and perhaps validation, data but poorly on test data) I thought I would throw more data at the problem; I combined all of the Twitter data collected to date (even though some of the code changed between various test runs) into a single data-set. This super-set contains 12861 generated compositions, 2651 of which were uploaded to twitter. I labelled samples as “good” where their score was greater than 100 (at least one like or RT and enough in person attention to upload to twitter). After filtering outliers (twice the system “saw” a face where there was no face, leading to very large and impossible attention values) this results in 1867 “good” compositions. When balancing the classes, the total set ends up with 3734 “good” and “bad” samples. Still not very big compared to my hand-labelled 15,000 sample pilot set, which contained 3971 “good” compositions. The amalgamated super-set was used for a number of experiments as follows.


60 wrd/min art critic (October 14th, 2020)

COVID19 Art Review. Lori Waxman, 60 wrd/min art critic.

Revisiting ML for Zombie Formalist

Posted: October 1, 2020 at 11:30 am

Since my past post on ML for the ZF, I’ve been running the system on Twitter and collecting data. The assumption being that the model’s lack of ability to generalize (work accurately for the test set) is due to a lack of data. Since classes are imbalanced, there are a lot of “bad” compositions compared to “good” ones, I end up throwing out a lot of generated data.

In the previous experiment I balanced classes only by removing samples that had very low attention. I considered these spurious interactions and thought they would just add noise. That data-set (E) had 568 good and 432 bad samples. The results of this most recent experiment follow.


Draft of Enclosure Design Ready for Quote Requests!

Posted: October 1, 2020 at 10:32 am

This most recent iteration of the case design is very close to finalized! There are still some tweaks, but I’m confident not too many changes will be needed. I’ve already sent this design off to a few local fabricators and only then will I have a good sense of where my budget lands and how many painting appropriation prints I can make!