7.00.02 - SupervisedShapeletClassifier Arguments - Aster Analytics

Teradata Aster® Analytics Foundation User GuideUpdate 2

Aster Analytics
Release Number
September 2017
Content Type
Programming Reference
User Guide
Publication ID
English (United States)
Last Update
[Optional] Specifies the name of the time_series column that contains the data points in the time series. Default: "value".
[Optional] Specifies the number of data points in a time series to skip between consecutive time series windows when calculating the distance of a shapelet from a time series.

Because a shapelet is typically much smaller than a complete time series, the function calculates the distance of a shapelet from a time series by sliding the shapelet across time series windows of shapelet length, calculating the distance between the shapelet and each window, and then selecting the smallest distance.

The num_data_points is the number of data points to skip when sliding from one time series window to the next. The num_data_points must be an INTEGER in the range [1, 1000000]. The value 1 gives optimal results at the cost of higher execution time. Default: 10.

This argument must specify the same value as the SupervisedShapeletTrainer TimeInterval argument specified when it generated the shapelets table.
[Optional] Specifies the names of the time_series columns to copy to the output table. Default: id and predicted_category. Columns specified by this argument appear after the other output table columns.