### Abstract

How do people determine which elements of a set are most representative of that set? We extend an existing Bayesian measure of representativeness, which indicates the representativeness of a sample from a distribution, to define a measure of the representativeness of an item to a set. We show that this measure is formally related to a machine learning method known as Bayesian Sets. Building on this connection, we derive an analytic expression for the representativeness of objects described by a sparse vector of binary features. We then apply this measure to a large database of images, using it to determine which images are the most representative members of different sets. Comparing the resulting predictions to human judgments of representativeness provides a test of this measure with naturalistic stimuli, and illustrates how databases that are more commonly used in computer vision and machine learning can be used to evaluate psychological theories.

Original language | English (US) |
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Title of host publication | Advances in Neural Information Processing Systems 24 |

Subtitle of host publication | 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011 |

State | Published - Dec 1 2011 |

Externally published | Yes |

Event | 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011 - Granada, Spain Duration: Dec 12 2011 → Dec 14 2011 |

### Publication series

Name | Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011 |
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### Other

Other | 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011 |
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Country | Spain |

City | Granada |

Period | 12/12/11 → 12/14/11 |

### All Science Journal Classification (ASJC) codes

- Information Systems

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## Cite this

*Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011*(Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011).