A Simple Relational Classifier

Abstract

We analyze a Relational Neighbor (RN) classifier, a simple relational predictive model the predicts only based on class labels of related neighbors, using no learning and no inherent attributes. We show that it performs surprisingly well by comparing it to more complex models such as Probabilistic Relational Models and Relational Probability Trees on three data sets from published work. We argue that a simple model such as this should be used as a baseline to assess the performance of relational learners.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2003
Accession Number
ADA452802

Entities

People

  • Foster Provost
  • Sofus A. Macskassy

Organizations

  • New York University

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Algorithms
  • Case Studies
  • Classification
  • Commerce
  • Computer Science
  • Data Science
  • Data Sets
  • Databases
  • Feature Selection
  • Machine Learning
  • New York
  • Relational Database Management Systems
  • Students
  • Test Sets
  • United States

Fields of Study

  • Computer science

Readers

  • Neural Network Machine Learning.