BP-MLL loss function for tensorflow
Efficient (vectorized) implementation of the BP-MLL loss function in TensorFlow (
BP-MLL is a loss function designed for multi-label classification using neural networks. It was introduced by Zhang & Zhou in . Note that in line with , every sample needs to have at least one label and no sample may have all labels.
pip3 install bpmll
from bpmll import bp_mll_loss
Then simply use it as a function in your tensorflow or keras models.
full_example.py for an example of training a simple multilayer perceptron using Keras with BP-MLL.
 Zhang, Min-Ling, and Zhi-Hua Zhou. "Multilabel neural networks with applications to functional genomics and text categorization." IEEE transactions on Knowledge and Data Engineering 18.10 (2006): 1338-1351.
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