Some Baselines for other Tabular Datasets with fastai2

[muellerzr (Zachary Mueller)]

Said post:

Feature importance in deep learning

FYI, here’s how I got at least the model-agnostic KernelExplainer from shap to run in a notebook without errors on a tabular learner (model/data on gpu with both categorical and continuous variables): # learn = tabular_learner(...) # learn.fit_one_cycle(...) import numpy as np import pandas as pd import shap shap.initjs() def pred(data): device = learn.data.device cat_cols = len(learn.data.train_ds.x.cat_names) cont_cols = len(learn.data.train_ds.x.cont_names) x_cat = torch.fr…

(But obviously I’ll make a notebook describing it)