Alexander Geiger
Alexander Geiger
One significant part of Orion is the user interaction, where users can annotate signals through MTV. We can use these annotations to improve future anomaly detections. A simple proposal of...
As mentioned in issue #72, we would like to implement a feedback integration module in Orion which uses subsequence shape matching. Basically any suitable method could be used, therefore we...
### Description We want to be able to train and predict our model several times in a moving manner, meaning we want to train a model and predict anomalies for...
There are a few things in the original NASA project/paper that are a bit confusing, so I will list them here for your information and future reference: - The labels...
In the original implementation a prediction window of size 10 is used. However, only the first value of that prediction sequence is used for the error calculation. I am not...
In the original implementation more than one input dimensions is used. We are currently only using the telemetry value itself, but there are some additional command dimensions in the raw...
### Description In the original paper a f0.5 score is used for evaluating the result. We might want to add that metric as well. sklearn.metrics.fbeta_score with beta=0.5 should achieve that.
The `rolling_window_sequences` primitive is not allowing a `target_size` of 0, in which case an out-of-bounds error will be raised for the line `y_index.append(index[end])`. The reason is the way we iterate...
### Description A low pass filter (in this example a [butterworth filter](https://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.signal.butter.html)) for the preprocessing of time series data. The outcome of such a filter should be similar to the...