Thank you @sheiser1
I found this
I have ư questions, hope get advice from you and others in thí forum
- is there any quickstart for above anomaly detection algorithm code
- in the above code they use the active columns and predicted columns to calculate the anomaly score. But as i know the output of SP is active columns indecies í ok but the output of TM is predicted cells (not columns). Can any one explain ?
Thank you very much
Anomaly ( slidingWindowSize=None , mode=‘pure’ , binaryAnomalyThreshold=None )
compute ( activeColumns , predictedColumns , inputValue=None , timestamp=None )¶
Compute the anomaly score as the percent of active columns not predicted.
Parameters: * activeColumns – array of active column indices
- predictedColumns – array of columns indices predicted in this step (used for anomaly in step T+1)
- inputValue – (optional) value of current input to encoders (eg “cat” for category encoder) (used in anomaly-likelihood)
timestamp – (optional) date timestamp when the sample occured (used in anomaly-likelihood)
Returns: the computed anomaly score; float 0…1