Percy Liang:机器学习的可解释性如此重要,我在努力,我们都需要努力 | 雷锋网

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Percy Liang 和团队针对这个问题提出的方法是尝试沿着模型的学习算法追踪模型的预测,一直反向追踪到模型参数产生的源头。他们希望这种方法——从训练数据的视角审视模型——可以成为开发、理解、诊断机器学习的标准方法的一部分。

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