LoopyBeliefPropagation Examples - 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
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B700-4003
lifecycle
previous
Product Category
Teradata Vantageā„¢

These examples use the LoopyBeliefPropagation function to determine the marginal probability of the disease hepatitis by observing its symptoms.

Hepatitis is an inflammation of the liver that can be caused by drugs, alcohol, or (most often) a virus. These are the most common symptoms of hepatitis:

  • Jaundice (yellowing of the skin and whites of the eyes)
  • Internal bleeding
  • Loss of appetite
  • Fatigue
  • Fever
  • Dark urine
  • Stupor
  • Nausea/vomiting

Given the presence or absence of a given symptom, the LoopyBeliefPropagation function determines the conditional or marginal probability of hepatitis.

The following figure shows the DAG that represents the relationship between hepatitis and its symptoms. The DAG represents each symptom by a conditional node and the disease by the dependent, unobserved node. These examples assume that each observed node variable is independent and binary.

Relationship between Hepatitis and Symptoms
Diagram of relationship between hepatitis and symptoms for Machine Learning Engine function LoopyBeliefPropagation examples