vanhavel/bp-mll-tensorflow

Implementation of the BP-MLL loss function in Tensorflow

bp-mll-tensorflow

Efficient (vectorized) implementation of the BP-MLL loss function in TensorFlow (bp_mll.py).

BP-MLL is a loss function designed for multi-label classification using neural networks. It was introduced by Zhang & Zhou in [1]. Note that in line with [1], every sample needs to have at least one label and no sample may have all labels.

Installation

pip3 install bpmll

Usage

from bpmll import bp_mll_loss

Then simply use it as a function in your tensorflow or keras models.

Check out full_example.py for an example of training a simple multilayer perceptron using Keras with BP-MLL.

References

[1] 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.