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I am working on a multi-label classification task. Most of the feature values are zero. The dataset is a binary vector. When I tried to generate the counterfactual, I got the error like sparse array length is ambiguous; use getnnz() or shape[0]
import numpy as np
e = dice.generate_counterfactuals(data, total_CFs=5, desired_class=1)
e.visualize_as_dataframe(show_only_changes=True)
The text was updated successfully, but these errors were encountered:
CTI2023
changed the title
parse array length is ambiguous; use getnnz() or shape[0]
sparse array length is ambiguous; use getnnz() or shape[0]
Oct 31, 2024
I am working on a multi-label classification task. Most of the feature values are zero. The dataset is a binary vector. When I tried to generate the counterfactual, I got the error like sparse array length is ambiguous; use getnnz() or shape[0]
import numpy as np
e = dice.generate_counterfactuals(data, total_CFs=5, desired_class=1)
e.visualize_as_dataframe(show_only_changes=True)
The text was updated successfully, but these errors were encountered: