Hi, i am experiencing something wierd. Not sure if I have done everything correctly and in the right order.
Using the Titanic data from Kaggle. Using fastai v1+.
procs = [FillMissing, Categorify, Normalize]
cat_names = ['Pclass','Sex', 'Title', 'SibSp', 'Parch','Embarked','Cabin']
cont_names = ['Age', 'Fare']
dep_var = 'Survived'
data = (TabularList.from_df(train_df_new, procs=procs, cont_names=cont_names, cat_names=cat_names)
.split_by_idx(valid_idx=range(len(train_df_new)-89,len(train_df_new)))
.label_from_df(cols=dep_var)
.add_test(TabularList.from_df(test_df_new, cat_names=cat_names, cont_names=cont_names, procs=procs))
.databunch())
learn = tabular_learner(data, layers=[200,100], metrics=accuracy)
learn.fit_one_cycle(5, 1e-3)
preds, y = learn.get_preds(ds_type=DatasetType.Test)
My y results are all zeros(as in all dead) when predicting on the Test dataset!
y
tensor([0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\
..........]
But pred p values are very low
tensor([[9.0810e-01, 9.1897e-02],
[6.5247e-01, 3.4753e-01],
[9.5031e-01, 4.9685e-02],
[9.0966e-01, 9.0339e-02],
[5.7985e-01, 4.2015e-01],
[8.8298e-01, 1.1702e-01],
What could be going on?