Improved Heterogeneous Distance Functions

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چکیده

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Improved Heterogeneous Distance Functions

Instance-based learning techniques typically handle continuous and linear input values well, but often do not handle nominal input attributes appropriately. The Value Difference Metric (VDM) was designed to find reasonable distance values between nominal attribute values, but it largely ignores continuous attributes, requiring discretization to map continuous values into nominal values. This pa...

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Distribution of material density and other properties of heterogeneous objects can be parametrized by the Euclidean distance function from the object boundary or from special material features. For objects constructed using geometric primitives and set-theoretic operations, an approximation of the distance function can be obtained in a constructive manner by applying special compositing operati...

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Constructive heterogeneous object modeling using signed approximate real distance functions

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Benefit and Distance Functions

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Multiplicative Distance Functions

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ژورنال

عنوان ژورنال: Journal of Artificial Intelligence Research

سال: 1997

ISSN: 1076-9757

DOI: 10.1613/jair.346