nam:神经加性模型（Google研究）
NAM：神经加性模型-可解释的机器学习与神经网络
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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]
文件下载
资源详情
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