Abstract
In previous work [3]we presented1BC, a first-order Bayesian classifier. 1BC applies dynamic propositionalisation, in the sense that attributes representing first-order features are generated exhaustively within a given feature bias, but during learning rather than as a pre-processing step. In this paper we describe 1BC2, which learns from structured data by fitting various parametric distributions over sets and lists to the data.We evaluate the feasibility of the approach by various experiments.
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Lachiche, N., Flach, P.A. (2003). 1BC2: A True First-Order Bayesian Classifier. In: Matwin, S., Sammut, C. (eds) Inductive Logic Programming. ILP 2002. Lecture Notes in Computer Science(), vol 2583. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36468-4_9
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DOI: https://doi.org/10.1007/3-540-36468-4_9
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