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ISIPTA

2005

IEEE

2005

IEEE

When considering sampling models described by a distribution from an exponential family, it is possible to create two types of imprecise probability models. One is based on the corresponding conjugate distribution and the other on the corresponding predictive distribution. In this paper, we show how these types of models can be constructed for any (regular, linear, canonical) exponential family, such as the centered normal distribution. To illustrate the possible use of such models, we take a look at credal classiﬁcation. We show that they are very natural and potentially promising candidates for describing the attributes of a credal classiﬁer, also in the case of continuous attributes. Keywords. Exponential family, Imprecise probability models, Inference, Conjugate analysis, Naive credal classiﬁer.

Related Content

Added |
25 Jun 2010 |

Updated |
25 Jun 2010 |

Type |
Conference |

Year |
2005 |

Where |
ISIPTA |

Authors |
Erik Quaeghebeur, Gert de Cooman |

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