nam:神经加性模型(Google研究)

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NAM:神经加性模型-可解释的机器学习与神经网络 | | NAM是用于广义加性模型研究的库。 神经加性模型(NAM)将DNN的某些表达能力与广义加性模型的固有清晰度结合在一起。 NAM学习神经网络的线性组合,每个神经网络都参与一个输入功能。 这些网络经过共同训练,可以学习其输入特征和输出之间的任意复杂关系。 概述 去做: 用法 $ python main.py -h usage: Neural Additive Models [-h] [--training_epochs TRAINING_EPOCHS] [--learning_rate LEARNING_RATE] [--output_regularization OUTPUT_REGULARIZATION]

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