The author sets the solver to saga, doesn’t standardize the features, and uses a very high max_iter.
Logistic Regression takes longer to converge when features are not standardized.
Also, the zstd classifier time complexity scales linearly with the number of classes, logistic regression doesn’t. You have 20 (it’s in the name of the dataset), so why only use 4.
It’s a cool exploration of zstd. But please give the baseline some love. Not everything has to be better than something to be interesting.
You are correct. To be fair I wasn't focused on comparing the runtimes of both methods. I just wanted to give a baseline and show that the batch approach is more accurate.
Comments
The speed comparison is weird.
The author sets the solver to saga, doesn’t standardize the features, and uses a very high max_iter.
Logistic Regression takes longer to converge when features are not standardized.
Also, the zstd classifier time complexity scales linearly with the number of classes, logistic regression doesn’t. You have 20 (it’s in the name of the dataset), so why only use 4.
It’s a cool exploration of zstd. But please give the baseline some love. Not everything has to be better than something to be interesting.
You are correct. To be fair I wasn't focused on comparing the runtimes of both methods. I just wanted to give a baseline and show that the batch approach is more accurate.
Yeah sorry, reading it back I was a bit too harsh haha. It was my pre-coffee comment. Nice post!