The time series feature derivation log provides details about the feature generation process for a time series project. It includes information about which features are generated and their priority, as well as the detected properties of the time series data such as whether the series is stationary, and periodicities detected.
character. Either (1) a character string giving the unique alphanumeric identifier for the project, or (2) a list containing the element projectId with this identifier.
integer. Optional. Default is 0. This many results will be skipped.
integer. Optional. Defaults to 100. At most this many results are returned. To specify no limit, use 0. The default may change without notice.
This route is only supported for time series projects that have finished partitioning. The time series feature log will include information about:
Detected stationarity of the series (e.g. "Series detected as non-stationary")
Detected presence of multiplicative trend in the series (e.g., "Multiplicative trend detected")
Any periodicities (e.g., "Detected periodicities: 7 day")
Maximum number of feature to be generated (e.g., "Maximum number of feature to be generated is 1440")
Window sizes used in rolling statistics / lag extractors (e.g., "The window sizes chosen to be: 2 months") (because the time step is 1 month and Feature Derivation Window is 2 months)
Features that are specified as known-in-advance (e.g., "Variables treated as known in advance: holiday")
Details about why certain variables are transformed in the input data (e.g., "Generating variable "y (log)" from "y" because multiplicative trend is detected")
Details about features generated as time series features, and their priority (e.g., "Generating feature "date (actual)" from "date" (priority: 1)")
Returns the feature log output
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## Not run: projectId <- "5984b4d7100d2b31c1166529" GetTimeSeriesFeatureDerivationLog(projectId) ## End(Not run)
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