I’m trying to use Fast.AI Tabular with Dice and Accuracy as metrics, but they do not work.
It works, but the result is weird.
Every epoch shows 0.5 AUROC, even when I tried 20 epochs.
But, when I calculated AUROC with valid values manually(with sklearn package), it was not 0.5, but about 0.8.
How can I fix this?
When I run, I get this error.
However, my data set has only float and category. I don’t know what “Long” is in my data.
Of course, I tried to change “category” to “float” because those columns have numbers as a category, but the result is the same.
When I run with “accuracy” as a metric, I get this error.
As you can see, it requires “Long” but it says that my data has “float”
It’s totally opposite to what I got in “dice”. It’s really weird.
Among the three metrics, AUROC is the most important to me now because I have to submit my result with this metric.
And this is my code for fastai and dataset.
dep_var = ‘isFraud’
cat = [‘card1’, ‘card2’, ‘card3’, ‘card4’, ‘card5’, ‘card6’, ‘addr1’, ‘addr2’]
cat_names = [e for e in cat if e in train.columns.tolist()]
cont = train.columns.tolist()
cont_names = [e for e in cont if e not in (cat)]
procs = [FillMissing, Categorify, Normalize]
path = base_dir
data = TabularDataBunch.from_df(path, train, dep_var,procs =procs, valid_idx=val_idx, test_df=test, cat_names=cat_names, cont_names=cont_names)
learn = tabular_learner(data, layers=[50,25], metrics=[AUROC()], y_range=[0,1])
learn = tabular_learner(data, layers=[50,25], metrics=[accuracy], y_range=[0,1])
If you need more information to check this error, please let me know.
Thank you so much in advance.