Why the predict samples of high energy as anomalies?

[HongminWu]

Dear author,
Recently, I am reading the paper of the DaGMM model and reproducing your code. A confusion is why the predict samples of high energy as anomalies? As I have known, the energy represents the likelihood of samples which should reflect how likely the samples can be modeled. Therefore, if our training dataset using normal samples, the testing samples with high energy/likelihood would be indicated as normal. Is it a correct expression?

[eat-toast]

Hi,
I think E(z) is caused.

when you look E(z)'s equation, there is a minus sign.

so, In OBJECT FUNCTION we minimize E(z) == find MLE.
and In Anomaly Detection, max E(z) == low Likelihood.