Path and Pattern Analysis Functions | Teradata Vantage - Path and Pattern Analysis - Teradata Vantage

Machine Learning Engine Analytic Function Reference

Product
Teradata Vantage
Release Number
9.02
9.01
2.0
1.3
Published
February 2022
Language
English (United States)
Last Update
2022-02-10
dita:mapPath
rnn1580259159235.ditamap
dita:ditavalPath
ybt1582220416951.ditaval
dita:id
B700-4003
lifecycle
previous
Product Category
Teradata Vantage™
Function Description
Attribution_MLE (ML Engine) Calculates attributions with a wide range of distribution models. Often used in web-page analysis.
FrequentPaths (ML Engine) Finds patterns that appear more than specified number of times in sequence database. Difference between sequential pattern mining and frequent pattern finding is that the former works on time sequences where order of items must be kept.
nPath® (ML Engine) Pattern-matching function that lets you to specify a pattern in a row sequence, specify additional conditions on the rows matching the symbols, and extract useful information from the row sequence.
Sessionize_MLE (ML Engine) Maps each click in clickstream to unique session identifier.
Hidden Markov Model Functions (ML Engine) Describes the evolution of observable events that depend on factors not directly observable.
Path Analysis Functions (ML Engine) Automate path analysis. Useful for clickstream analysis of web site traffic and other sequence/path analysis tasks, such as advertisement or referral attribution.
Shapley Value Functions (ML Engine) Computes the Shapley value, typically from nPath function output. The Shapley value is intended to reflect the importance of each player to the coalition in a cooperative game (a game between coalitions of players, rather than between individual players).