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Autoencoder

test of AE 测试自动编码器的效果,参考论文《Autoencoder-based_Intrusion_Detection_System》
一维的AE效果还可以,基本达到了原文所述的效果
结构如下:
image
训练集仅由正常数据组成,验证集仅由异常数据组成,可以看到两者的重建误差之间存在明显距离:
image
测试集由近乎1:1的正常数据和异常数据组成,其重建loss分布如下:
image
优化得到最佳阈值:0.025,在第二个测试集上进行验证:
image

均可以得到还不错的效果;

然后尝试了使用zigzag预处理,并用全卷积搭建CAE,但是得到的效果不如人意,可能是因为在zigzag过程中数据细节被过分放大,导致模型过拟合,在训练阶段正常数据与异常数据仍然存在较大的重建误差差距,但是应用到测试集的时候,这种差距并不明显,准确率下降到只有58%左右,zigzag可能并不适合无监督学习(争议
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