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        "author": "Lukas Huwald",
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        "description": "# bp-mll-tensorflow\nEfficient (vectorized) implementation of the BP-MLL loss function in TensorFlow (```bp_mll.py```). \n\nBP-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.\n\n# Installation \n`pip3 install bpmll`\n\n# Usage\n```\nfrom bpmll import bp_mll_loss\n```\nThen simply use it as a function in your tensorflow or keras models.\n\nCheck out ```full_example.py``` for an example of training a simple multilayer perceptron using Keras with BP-MLL.\n\n# References\n[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.\n\n\n",
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