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Numpy arrays and Unknown label type: 'continuous' #16
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Hi Clement, thank you for your suggestions.
Thank you, |
Hi Florian, Thanks for your answer. It's occuring when I use the pps on timeseries extracted from an fMRI.
and it returned me the following matrix:
|
Thank you for the example. When passing a task to the matrix, this bypasses the logic for the diagonal I would love to see your example with the timeseries data in case that it is not under an NDA. If you want, we could have a quick video session about it Florian |
Sorry for the delay, |
To summarize this issue:
If you want to discuss the pps in neuroimaging, please open a new issue :) |
Hi,
I'm quickly experimenting by implementing ppscore in my pipeline for the assessment of functional connectivity between brain regions, and I noticed two things:
1/ I think we should be able to use pps.matrix() even on a 2D numpy array when we don't have explicit column names: as of now, it is raising the error
AttributeError: 'numpy.ndarray' object has no attribute 'columns'
2/ I got a strange error telling me that "continuous" is an unknown label.
File "/home/clementpoiret/anaconda3/envs/nilearn/lib/python3.8/site-packages/sklearn/utils/multiclass.py", line 172, in check_classification_targets raise ValueError("Unknown label type: %r" % y_type) ValueError: Unknown label type: 'continuous'
Code to reproduce the error:
The error is solved by passing
task='regression'
. I have sklearn 0.23.0Maybe an additional comment: maybe that the diagonal of the resulting matrix should be 1, because it makes sense that the predictive power of a vector on itself is 1, no?
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