[BUG] model.fit leads to TypeError

[jbottke]

Describe the bug
When trying to fit a classification model on the adult census dataset, the training process results in a TypeError while trying to concatenate an integer to a string in datamodule.py

To Reproduce

• load adult census dataset using shapiq with shapiq.datasets.load_adult_census()
• preprocess data using sklearns train_test_split() function which shuffles dataset und splits it into four numpy arrays (x_train, x_test, y_train, y_test)
• create Instance of MambularClassifier and fit it on numpy arrays x_train, y_train

Expected behavior
Method is expected to further process training data and use it to train model. After that, the best model parameters are expected to be saved under model_checkpoints.

Screenshots

Desktop:

• OS: Ubuntu via WSL2
• Python version 3.10.12
• Mambular Version 1.1.0

[jbottke]

One is able to avoid the Problem by converting x_train from a numpy array to a pandas dataframe with named columns. It is important for the columns of the dataframe to be Strings. y_train can be a numpy array after all.

[AnFreTh]

Thanks again for raising this issue! The latest release v1.2.0 #222 should solve this issue. Feel free to reopen or open any other issues if you encounter any more bugs.