All Questions
6 questions
2votes
1answer
750views
Early anomaly detection / Failure prediction on time series
My problem here is that I want to predict failures in advance with respect to their occurrence. I have sensors mounted on my machine and with a certain frequency, they send data to my database. ...
- 45
1vote
2answers
267views
Autenocoder and anomaly detection task
I'm trying to create an autoencoder for the anomaly detection task, but I'm noticing that even if it performs very well on the training set, it starts to stop recreating half of the test set. I tried ...
- 53
0votes
1answer
412views
Understanding time series anomaly detection using Autoencoder
I'm studying how to detect anomalies in the time series using an Autoeconder. In particular, I'm following the guide posted in the Keras website, but I don't understand why they are creating and how ...
- 53
1vote
1answer
217views
SPC vs Autoencoders in anomaly detection
Considering the usage of Autoencoders in anomaly detection of time-series data, why SPCs (control charts) have lost their charm? Are there any advantages with Autoencoders and disadvantages with SPCs?
- 153
2votes
0answers
135views
Can autoencoders take time series into account?
Here, I read the following: The first key to understanding is that HTM relies on data that streams over time (...) By contrast, conventional deep learning uses static data and is therefore time ...
- 570
1vote
0answers
1kviews
H2o autoencoder anomaly detection for multivariate time series data
I am applying H2o autoencoder for anomaly detection for multivariate time series data. I have many time series data for different metrics of network elements which are recorded every 15 minutes. I ...
