Feature selection methods for solving the reference class problem

Columbia Law Review Sidebar 110:12-23 (2010)
  Copy   BIBTEX

Abstract

Probabilistic inference from frequencies, such as "Most Quakers are pacifists; Nixon is a Quaker, so probably Nixon is a pacifist" suffer from the problem that an individual is typically a member of many "reference classes" (such as Quakers, Republicans, Californians, etc) in which the frequency of the target attribute varies. How to choose the best class or combine the information? The article argues that the problem can be solved by the feature selection methods used in contemporary Big Data science: the correct reference class is that determined by the features relevant to the target, and relevance is measured by correlation (that is, a feature is relevant if it makes a difference to the frequency of the target).

Author's Profile

James Franklin
University of New South Wales

Analytics

Added to PP
2019-10-10

Downloads
186 (#40,585)

6 months
39 (#25,468)

Historical graph of downloads since first upload
This graph includes both downloads from PhilArchive and clicks on external links on PhilPapers.
How can I increase my downloads?