Learning acyclic probabilistic logic programs from data.

Learning acyclic probabilistic logic programs from data.

To learn a probabilistic logic program is to find a set of probabilistic rules that best fits some data, in order to explain how attributes relate to one another and to predict the occurrence of new instantiations of these attributes. In this work, we focus on acyclic programs, because in this case...

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Bibliographic Details
Main Author: Faria, Francisco Henrique Otte Vieira de
Other Authors: Cozman, Fabio Gagliardi
Format: Others
Language:en
Published: Biblioteca Digitais de Teses e Dissertações da USP 2017
Subjects:
Aprendizado computacional
Explainable AI
Machine learning
Probabilistic logic programming
Programação lógica
Online Access:http://www.teses.usp.br/teses/disponiveis/3/3141/tde-27022018-090821/

Internet

http://www.teses.usp.br/teses/disponiveis/3/3141/tde-27022018-090821/

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