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Bayesian methods for nonlinear classification and regression
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Bayesian methods for nonlinear classification and regression

by David G. T. Denison, Christopher C. Holmes, Bani K. Mallick, Adrian F. M. Smith

An exploration of nonlinear modelling and Bayesian methods, this text focuses on classification and regression. It covers neural networks, decision trees, and splines, presenting practical applications in medicine, economics, and spatial analysis.

Accession 5778 ISBN 0471490369 Publisher John Wiley & Sons
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position_updated_at
2026-06-01 16:32
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Hard Back
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spine_text
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LOCATION HISTORY
M:N3:2 4 Current vertical
2 weeks ago
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Identity

name→ title
Bayesian methods for nonlinear classification and regression
vernon_id
9587
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5778
vernon_slug
bayesian-methods-for-nonlinear-classification-and-regression-david-g-t-denison-christopher-c-holmes-bani-k-mallick-adrian-f-m-smith

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isbn_issn→ isbn (when valid)
0471490369

Descriptive

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2002
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brief_description
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Subjects & people

authors→ author (initial fill only)
David G. T. Denison, Christopher C. Holmes, Bani K. Mallick, Adrian F. M. Smith
tags→ tags
Science, Mathematics, Statistics, Sampling (Statistics), Bayesian statistical decision theory, Statistical decision, Statistical matching
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18894

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