Attribute-Value and Relational Learning: A Statistical Viewpoint

James Cussens

Attribute-Value and Relational Learning: A Statistical Viewpoint

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this extended abstract, rather than crossing the boundary between attribute-value and relational learning, we place ourselves above any such boundary and look down on the problem from the point of view of general principles of statistical inference. We do not pretend that this paper gives a full account of all relevant issues, but argue that starting from this generalised viewpoint and working down towards actual learning problems (e.g. decision tree learning, regression, ILP, etc) makes it easier to find the essential contrasts and similarities between different learning problems. Our primary goal (not achieved here) is to abstract away from superficial issues, such as the concrete syntactic representation of a problem or worse the sociological origin of an approach.

Original language	English
Title of host publication	Proceedings of the ICML-2000 Workshop on Attribute-Value and Relational Learning: Crossing the Boundaries
Editors	Luc De Raedt, Stefan Kramer
Pages	35-39
Number of pages	5
Publication status	Published - 2000

Access to Document

http://www.informatik.uni-freiburg.de/~ml/icml2000_workshop/cussens.ps

Cite this

@inproceedings{15d08330be7145409f6dadc72004461c,

title = "Attribute-Value and Relational Learning: A Statistical Viewpoint",

abstract = "In this extended abstract, rather than crossing the boundary between attribute-value and relational learning, we place ourselves above any such boundary and look down on the problem from the point of view of general principles of statistical inference. We do not pretend that this paper gives a full account of all relevant issues, but argue that starting from this generalised viewpoint and working down towards actual learning problems (e.g. decision tree learning, regression, ILP, etc) makes it easier to find the essential contrasts and similarities between different learning problems. Our primary goal (not achieved here) is to abstract away from superficial issues, such as the concrete syntactic representation of a problem or worse the sociological origin of an approach.",

author = "James Cussens",

year = "2000",

language = "English",

pages = "35--39",

editor = "{De Raedt}, Luc and Stefan Kramer",

booktitle = "Proceedings of the ICML-2000 Workshop on Attribute-Value and Relational Learning: Crossing the Boundaries",

}

TY - GEN

T1 - Attribute-Value and Relational Learning: A Statistical Viewpoint

AU - Cussens, James

PY - 2000

Y1 - 2000

N2 - In this extended abstract, rather than crossing the boundary between attribute-value and relational learning, we place ourselves above any such boundary and look down on the problem from the point of view of general principles of statistical inference. We do not pretend that this paper gives a full account of all relevant issues, but argue that starting from this generalised viewpoint and working down towards actual learning problems (e.g. decision tree learning, regression, ILP, etc) makes it easier to find the essential contrasts and similarities between different learning problems. Our primary goal (not achieved here) is to abstract away from superficial issues, such as the concrete syntactic representation of a problem or worse the sociological origin of an approach.

AB - In this extended abstract, rather than crossing the boundary between attribute-value and relational learning, we place ourselves above any such boundary and look down on the problem from the point of view of general principles of statistical inference. We do not pretend that this paper gives a full account of all relevant issues, but argue that starting from this generalised viewpoint and working down towards actual learning problems (e.g. decision tree learning, regression, ILP, etc) makes it easier to find the essential contrasts and similarities between different learning problems. Our primary goal (not achieved here) is to abstract away from superficial issues, such as the concrete syntactic representation of a problem or worse the sociological origin of an approach.

M3 - Conference contribution

SP - 35

EP - 39

BT - Proceedings of the ICML-2000 Workshop on Attribute-Value and Relational Learning: Crossing the Boundaries

A2 - De Raedt, Luc

A2 - Kramer, Stefan

ER -