Immune_All_Low - model training question about celltypist

[KatarinaLalatovic]

I am also interested in this

[ChuanXu1]

@NikicaJEa, if you only select a subset of genes for training, SGD is not necessary - you can safely turn it off to enable a canonical logistic regression.

[NikicaJEa]

Thanks for your reply @ChuanXu1. I experimented with all possible combinations I could think of: with/without SGD, mini batching, balance_cell_type, without subseting genes, with feature selection step. Unfortunately, none of these combinations yielded results comparable to the original immune_low model. Now I understand there is always some degree of randomness to be expected, but this is more than I would expect. It would be beneficial to understand the specific parameters under which the original model was trained.

[ChuanXu1]

@NikicaJEa, to produce a model with comparable performance versus the built-in models, you can use the same set of genes (which you had already done plus check_expression = False) and increase the number of iterations (for example, max_iter = 1000), with all other parameters being the defaults.