Comments (1)
So, here is the only rule: the larger reconstruction probability, the less likely a point
is an anomaly. You should not use absolute values.
Reconstruction probability may be positive or negative since it is the logarithm of the probability density and it can be ang real number actually.
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Related Issues (20)
- 关于test score的问题 HOT 1
- the length of test_score dosen't match that of length of test_values HOT 1
- the length of get_score is less than the length of test datas HOT 4
- Donut模型并行化的问题 HOT 1
- Understanding What Test Scores Mean HOT 1
- Size of prediction doesn't match size of test_values HOT 1
- sliding window HOT 1
- f-score for prediction is too bad HOT 1
- time series detection for multi dimensional time series? HOT 1
- why n_z in DonutPredictor has a default value 1024
- The dataset used in the paper that proposed Donut
- Training Loss is minus HOT 1
- Eef HOT 1
- cannot import name 'complete_timestamp' from 'donut' (C:\Users\HP\anaconda3\lib\site-packages\donut.py)
- 您好,最后predictor得到的score的含义是什么?
- Can it be used to multivariate time series anomaly detection?
- 论文中隐藏层3d图片是如何绘制出来的,
- 如何单独进行predict HOT 1
- AttributeError: module 'tensorflow' has no attribute 'GraphKeys' HOT 1
- About M-ELBO loss function
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