Open Sreedhanya-K opened 3 years ago
Hmm that's interesting, I didn't think there would be that much variability in the parameter estimates. We could probably help you more if you posted some sample data and the algorithm you're using to detect anomalies?
I also encountered this problem and I am very confused now. Have you solved it?
I use the official example, and the result of each run is different.
Hmm that's interesting, I didn't think there would be that much variability in the parameter estimates. We could probably help you more if you posted some sample data and the algorithm you're using to detect anomalies?
Hi:I use the official example, and the result of each run is different.Can u help me?The [upper & lower ] of results are different each time. yhat is all the same.
Hmm that's interesting, I didn't think there would be that much variability in the parameter estimates. We could probably help you more if you posted some sample data and the algorithm you're using to detect anomalies?
Hi:I use the official example, and the result of each run is different.Can u help me?The [upper & lower ] of results are different each time. yhat is all the same.
I have the same problem. I used a basic model that didn't adjust any parameters. The yhat is the same, but the lower and upper values continue to change.
I am using fbprophet for anomaly detection, and for the same data sets, the results are different for different runs in my laptop. The number of anomalies and the anomalies which the code pick up are different for 1st, 2nd third.. runs. I am confused, how can I use this , though it is giving good results many a times. The false positives are too many in a few runs. Can someone please help me to fix this. I have tried algorithm = 'Newton'. Still the result is not constant. Sree