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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
The text was updated successfully, but these errors were encountered:
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.
jbottke
changed the title
[BUG]
[BUG] model.fit leads to TypeError
Feb 11, 2025
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
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:
The text was updated successfully, but these errors were encountered: