On loss functions which minimize to conditional expected values and posterior probabilities

DOI10.1109/18.243457zbMath0799.62010OpenAlexW2157679397MaRDI QIDQ4307345

Padhraic Smyth, Rod Goodman, John W. Miller

Publication date: 4 October 1994

Published in: IEEE Transactions on Information Theory (Search for Journal in Brave)

Full work available at URL: https://authors.library.caltech.edu/93850/

zbMATH Keywords

necessary and sufficient conditionsobjective functionsquared-error losscross entropy loss\(P\)-admissibilitymean-square error losstraining neural networks

Mathematics Subject Classification ID

Statistical decision theory (62C99) Statistical aspects of information-theoretic topics (62B10) Admissibility in statistical decision theory (62C15)

Related Items (3)

Cost-sensitive learning based on Bregman divergences ⋮ Risk-sensitive loss functions for sparse multi-category classification problems ⋮ The asymptotic optimization of pre-edited ANN classifier

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