Hello Christoph,
I ran into an issue when running the dl-classifier.ipynb. I used the data you suggested in your README and basically wanted to see the results before using it on another data source. I was hoping you might've run into this earlier and could shed some light on this issue.
The error message I got was: recursionerror: maximum recursion depth exceeded while calling a Python object.
The code causing this is in 2.1 Data loading and preperation
X_train, y_train, X_val, y_val, X_test, y_test, column_names = transform_data(dataset=dataset,
imputer_strategy='median',
scaler=StandardScaler,
attack_samples=100000,
random_state=rand_state)
This is defined in notebook_utils.py, in which line 79 is where the issue is caused.
X_train, y_train = upsample_minority_classes(X_train,
y_train,
min_samples=attack_samples,
random_state=random_state)
I've tried debugging this for some time now and would find your input extremely valuable.
Thank you
Hello Christoph,
I ran into an issue when running the dl-classifier.ipynb. I used the data you suggested in your README and basically wanted to see the results before using it on another data source. I was hoping you might've run into this earlier and could shed some light on this issue.
The error message I got was: recursionerror: maximum recursion depth exceeded while calling a Python object.
The code causing this is in 2.1 Data loading and preperation
X_train, y_train, X_val, y_val, X_test, y_test, column_names = transform_data(dataset=dataset,
imputer_strategy='median',
scaler=StandardScaler,
attack_samples=100000,
random_state=rand_state)
This is defined in notebook_utils.py, in which line 79 is where the issue is caused.
X_train, y_train = upsample_minority_classes(X_train,
y_train,
min_samples=attack_samples,
random_state=random_state)
I've tried debugging this for some time now and would find your input extremely valuable.
Thank you