How to conduct anomaly detection in PyTorch?


import torch

# 创建一个包含随机数的张量
x = torch.randn(5, 5)

# 设置阈值
threshold = 2.0

# 检测异常值
mask = torch.abs(x) > threshold

# 打印异常值的索引

In the example above, we first create a tensor x containing random numbers, then set a threshold value. We then use the torch.abs function to obtain elements with absolute values greater than the threshold, and create a mask tensor. Finally, we use the torch.nonzero function to find the indices of the outliers and print them out.

This is just a simple example, more complex anomaly detection methods can be applied in actual use according to specific needs and data characteristics.

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