Arguments - Aster Analytics

Teradata Aster Analytics Foundation User Guide

Product
Aster Analytics
Release Number
6.21
Published
November 2016
Language
English (United States)
Last Update
2018-04-14
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kiu1466024880662.ditamap
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AA-notempfilter_pdf_output.ditaval
dita:id
B700-1021
lifecycle
previous
Product Category
Software
Argument Category Description
InputTable Required Specifies the name of the table that contains the input data.
CategoryTable Optional Specifies the name of the table that contains the categories (classes) for the time series in input_data_table. The default value is input_data_table.

If input_categories_table is different from input_data_table, the function ignores any time series that is not in both input_categories_table and input_data_table. If a time series is represented by multiple rows in input_categories_table, these rows must contain the same category; otherwise, the function might not select the correct category.

IDColumn Required Specifies the name of the column in input_data_table and input_categories_table that contains the unique identity of a time series.
TimeColumn Required Specifies the name of the input_data_table column that contains the time axis of the data.
ValueColumn Required Specifies the name of the input_data_table column that contains the data points.
CategoryColumn Required Specifies the name of the input_categories_table column that contains the category (class) of the time series.
SaxSymbolsPerWindow Optional Specifies the SAX2 argument SymbolsPerWindow, which specifies the number of SAX code symbols to generate from a window. The symbols_per_window must an INTEGER in the range [1, 1000000]. The default value is 10.

If the symbols_per_window is greater than the length of the shortest time series in input data set (d), then its value becomes d.

SaxMinWindowSize Optional Specifies the SAX2 argument WindowSize , which specifies the size of the sliding window. The min_window_size defines the length (number of data points) of the shortest shapelet; the minimum span (time series length) used to distinguish two time series from each other. The min_window_size must be an integer in the range [1, 1000000]. The default value is 10.

If the min_window_size is greater than the length of the shortest time series in input data set (d), then its value becomes d. If min_window_size is smaller than symbols_per_window, then its value becomes symbols_per_window.

SaxMaxWindowSize Optional Specifies the SAX2 argument WindowSize , which specifies the size of the sliding window. The max_window_size defines the length of the longest shapelet; the maximum span used to distinguish two time series from each other. The max_window_size must be an integer in the range [1, 1000000] that is greater than or equal to min_window_size. The default value is 70.

If the max_window_size is greater than the length of the shortest time series in input data set (d), then its value becomes d.

A greater difference between min_window_size and max_window_size increases the probability of identifying better shapelets at the cost of higher execution time. The function uses this formula to compute the number of sliding windows, n:

n = ((max_window_size min_window_size) / symbols_per_window)+1

The maximum value of n is 20.

SaxOutputFrequency Optional Specifies SAX2 argument OutputFrequency, which specifies the number of data points to skip between successive sliding windows. The gap_between_windows must be an integer in the range [1, 1000]. The default value is 10. A smaller value increases accuracy (the chance of distinguishing time series from each other) at the cost of higher execution time.
ModelTable Optional Specifies the name of the output model table that contains trained shapelets. The default output_model_table is "shapelet_model".
OverwriteOutput Optional Specifies whether to overwrite output_model_table, if it exists. The default value is 'false'.
RandomProjections Optional Specifies the number of iterations required for random masking of SAX words during shapelet training. The projections must be an INTEGER in the range [1, 40]. The default value is 10.

Specifying a greater projections for a longer input time series increases the probability of identifying better shapelets at the cost of higher execution time.

ShapeletCount Optional Specifies the maximum number of shapelets in the output model table. The num_shapelets must be an INTEGER in the range [1, 100000]. The default value is 20.
TimeInterval 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.

The function builds a shapelet classification tree based on the distance of a shapelet from the time series data. 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. The default value is 10.

Seed Optional Specifies the seed value for the function to use to generate random numbers, which it uses internally. The seed must be an INTEGER in the range [1, 100000]. The default value is 23.