1.1 - 8.10 - ChangePointDetection Syntax Elements - Teradata Vantage

Teradata Vantage™ - Machine Learning Engine Analytic Function Reference

Product
Teradata Vantage
Release Number
1.1
8.10
Release Date
October 2019
Content Type
Programming Reference
Publication ID
B700-4003-079K
Language
English (United States)
TargetColumn
Specify the name of the input table column that contains the time series data.
Accumulate
Specify the names of the input table columns to copy to the output table.
Tip: To identify change points in the output table, specify the columns that appear in partition_exp and order_by_exp.
SegmentationMethod
[Optional] Specify the segmentation method:
   
'normal_distribution' (Default) In each segment, data is in normal distribution.
'linear_regression' In each segment, data is in linear regression.
SearchMethod
[Optional] Specify the search method, binary search.
MaxChangeNum
[Optional] Specify the maximum number of change points to detect.
Default: 10
Cost
[Optional] Specify the penalty function, which is used to avoid over-fitting:
Option Condition for Change Point Existence Condition for Normal Distribution and Linear Regression
'BIC' (Default) ln(L 1)−ln(L 0) > (p 1 -p 0)*ln(n)/2 (p 1 -p 0)*ln(n)/2 = ln(n)
'AIC' ln(L 1)−ln(L 0) > p 1 -p 0

p 1 -p 0 = 2

threshold, a DOUBLE PRECISION value

Function compares specified value to ln(L 1)−ln(L 0).

L 1 and L 0 are the maximum likelihood estimation of hypotheses H 1 and H 0.

For normal distribution, the definition of Log(L 1 ) and Log(L 0) are in ChangePointDetection (ML Engine).  

p is the number of additional parameters introduced by adding a change point. p 1 and p 0 represent this parameter in hypotheses H 1 and H 0, respectively.

OutputType
[Optional] Specify the output table columns. See ChangePointDetection Output.
Default: 'CHANGEPOINT'