You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
I attempted to use mrmr_regression in a pipeline with gridsearchCV to optimize the argument K as a hyperparameter and ran into the following issue:
I made a function that would return just dataframe with a sparse feature set.
Then, I used FunctionTransformer to convert this into a transformer to be used in a pipeline.
After adding some arbitrary sklearn model (sklearn.kernel_ridge.KernelRidge), to the pipeline and trying to use gridsearchCV, it returned the following error: 'numpy.ndarray' object has no attribute 'columns'. The same error came up when trying to call "pipe.fit()" without gridsearchCV.
I think this is referring to the fact that your function 'parallel_df' called in 'f_regression' uses df.columns, and gridsearch might be trying to feed it a 2d array. Do you have any suggestions on how to get around this issue?
Thank you very much
The text was updated successfully, but these errors were encountered:
Hello,
I attempted to use mrmr_regression in a pipeline with gridsearchCV to optimize the argument K as a hyperparameter and ran into the following issue:
I made a function that would return just dataframe with a sparse feature set.
Then, I used FunctionTransformer to convert this into a transformer to be used in a pipeline.
After adding some arbitrary sklearn model (sklearn.kernel_ridge.KernelRidge), to the pipeline and trying to use gridsearchCV, it returned the following error: 'numpy.ndarray' object has no attribute 'columns'. The same error came up when trying to call "pipe.fit()" without gridsearchCV.
I think this is referring to the fact that your function 'parallel_df' called in 'f_regression' uses df.columns, and gridsearch might be trying to feed it a 2d array. Do you have any suggestions on how to get around this issue?
Thank you very much
The text was updated successfully, but these errors were encountered: