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Is Infidelity Predictable? Using Explainable Machine Learning to Identify the Most Important Predictors of Infidelity
Laura M. Vowels
, Matthew J. Vowels
,
Kristen P. Mark
Family Medicine and Community Health (Twin Cities)
Research output
:
Contribution to journal
›
Article
›
peer-review
31
Scopus citations
Overview
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Dive into the research topics of 'Is Infidelity Predictable? Using Explainable Machine Learning to Identify the Most Important Predictors of Infidelity'. Together they form a unique fingerprint.
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Computer Science
Machine Learning Algorithm
100%
Random Decision Forest
100%
Relationship Satisfaction
100%
Explainable Artificial Intelligence
100%
Relative Importance
100%
Predictor Variable
100%
Decision Tree
100%
Keyphrases
Explainable Machine Learning
100%
Infidelity
100%
Well-being
12%
Romantic Relationships
12%
Relationship Satisfaction
12%
Interpersonal Factors
12%
Relationship Length
12%
Highly Nonlinear
12%
Predictor Variables
12%
Relationship Difficulties
12%
Shapley Value
12%
Disruptive Events
12%
Internet Infidelity
12%
Game Analysis
12%
Nonlinear Decision Trees
12%
Machine Learning Algorithm Random Forest
12%
Psychology
Romantic Relationship
100%
Learning Algorithm
100%