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Not really a code related question, but more of a methods question.
Is there some material on the basic concepts that have been used to develop the luminol package? For example, whats the basic idea behind detecting the anomaly, how to interpret the score, how does the algorithm handles the seasonality and trend in the data. Should we make the time series stationary before using it? Or how does the package manages to work with data with non-stationary time series?
Thanks
The text was updated successfully, but these errors were encountered:
Not really a code related question, but more of a methods question.
Is there some material on the basic concepts that have been used to develop the luminol package? For example, whats the basic idea behind detecting the anomaly, how to interpret the score, how does the algorithm handles the seasonality and trend in the data. Should we make the time series stationary before using it? Or how does the package manages to work with data with non-stationary time series?
Thanks
The text was updated successfully, but these errors were encountered: