Decomposing probability distributions on structured individuals

Peter Flach; Paulo Brito; Lachiche Nicolas; Costa Joaquim; Donato Malerba

Decomposing probability distributions on structured individuals

Peter Flach, Paulo Brito, Lachiche Nicolas, Costa Joaquim, Donato Malerba

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

Abstract

Naive Bayesian classifiers are very successful in attribute-value representations. However, it is not clear how the decomposition of the probability distributions on attribute-value tuples underlying those classifiers can be applied on structured individuals, for instance sets of tuples as in the multiple instance problem. This paper presents a decomposition of probability distributions on structured individuals. It shows how it results in a propositionalisation of the data guided by the decomposition of the structure of the individual. This is illustrated by using the first-order naive Bayesian classifier 1BC to perform the decomposition of probability distributions on structured individuals.

Translated title of the contribution	Decomposing probability distributions on structured individuals
Original language	English
Title of host publication	Proceedings of the ECML2000 workshop on Dealing with Structured Data in Machine Learning and Statistics
Publisher	European Conference on Machine Learning
Publication status	Published - 2000

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Other page information: 33-43
Conference Proceedings/Title of Journal: Proceedings of the ECML2000 workshop on Dealing with Structured Data in Machine Learning and Statistics
Other identifier: 1000484

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@inproceedings{708c3f99deb1460d8760d20d36a04358,

title = "Decomposing probability distributions on structured individuals",

abstract = "Naive Bayesian classifiers are very successful in attribute-value representations. However, it is not clear how the decomposition of the probability distributions on attribute-value tuples underlying those classifiers can be applied on structured individuals, for instance sets of tuples as in the multiple instance problem. This paper presents a decomposition of probability distributions on structured individuals. It shows how it results in a propositionalisation of the data guided by the decomposition of the structure of the individual. This is illustrated by using the first-order naive Bayesian classifier 1BC to perform the decomposition of probability distributions on structured individuals. ",

author = "Peter Flach and Paulo Brito and Lachiche Nicolas and Costa Joaquim and Donato Malerba",

note = "Other page information: 33-43 Conference Proceedings/Title of Journal: Proceedings of the ECML2000 workshop on Dealing with Structured Data in Machine Learning and Statistics Other identifier: 1000484",

year = "2000",

language = "English",

booktitle = "Proceedings of the ECML2000 workshop on Dealing with Structured Data in Machine Learning and Statistics",

publisher = "European Conference on Machine Learning",

}

Decomposing probability distributions on structured individuals. / Flach, Peter; Brito, Paulo; Nicolas, Lachiche et al.
Proceedings of the ECML2000 workshop on Dealing with Structured Data in Machine Learning and Statistics. European Conference on Machine Learning, 2000.

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

TY - GEN

T1 - Decomposing probability distributions on structured individuals

AU - Flach, Peter

AU - Brito, Paulo

AU - Nicolas, Lachiche

AU - Joaquim, Costa

AU - Malerba, Donato

N1 - Other page information: 33-43 Conference Proceedings/Title of Journal: Proceedings of the ECML2000 workshop on Dealing with Structured Data in Machine Learning and Statistics Other identifier: 1000484

PY - 2000

Y1 - 2000

N2 - Naive Bayesian classifiers are very successful in attribute-value representations. However, it is not clear how the decomposition of the probability distributions on attribute-value tuples underlying those classifiers can be applied on structured individuals, for instance sets of tuples as in the multiple instance problem. This paper presents a decomposition of probability distributions on structured individuals. It shows how it results in a propositionalisation of the data guided by the decomposition of the structure of the individual. This is illustrated by using the first-order naive Bayesian classifier 1BC to perform the decomposition of probability distributions on structured individuals.

AB - Naive Bayesian classifiers are very successful in attribute-value representations. However, it is not clear how the decomposition of the probability distributions on attribute-value tuples underlying those classifiers can be applied on structured individuals, for instance sets of tuples as in the multiple instance problem. This paper presents a decomposition of probability distributions on structured individuals. It shows how it results in a propositionalisation of the data guided by the decomposition of the structure of the individual. This is illustrated by using the first-order naive Bayesian classifier 1BC to perform the decomposition of probability distributions on structured individuals.

M3 - Conference Contribution (Conference Proceeding)

BT - Proceedings of the ECML2000 workshop on Dealing with Structured Data in Machine Learning and Statistics

PB - European Conference on Machine Learning

ER -

Decomposing probability distributions on structured individuals

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