When labels are hierarchical and represented as a list of lists and all inner lists don't have equal length, numpy array constructor gives the following error
setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (1781,) + inhomogeneous part.
This happens in HierarchicalClassifier.py at line 164.
Seeing the line at 171, where you are leveling the labels, I wonder if it should be done before converting to numpy array.
For Sample data, where Y_train_modifed = [['a'], ['b', 'c']]
This code gives the above error.
lcppn2 = LocalClassifierPerParentNode(local_classifier=model, verbose=1, bert=True) lcppn2.fit(X_train, Y_train_modified)
When labels are hierarchical and represented as a list of lists and all inner lists don't have equal length, numpy array constructor gives the following error
This happens in HierarchicalClassifier.py at line 164.
Seeing the line at 171, where you are leveling the labels, I wonder if it should be done before converting to numpy array.
For Sample data, where
Y_train_modifed = [['a'], ['b', 'c']]This code gives the above error.
lcppn2 = LocalClassifierPerParentNode(local_classifier=model, verbose=1, bert=True) lcppn2.fit(X_train, Y_train_modified)hi-class version: 4.12.1 numpy version: 1.26.4