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Learning from Data

Name: Learning from Data
Brand: Springer-Verlag New York Inc.
SKU: 9780387947365
Price: 2286 CZK
Availability: InStock

Artificial Intelligence and Statistics V

Autor: Doug Fisher, Hans-J. Lenz

Jazyk:

Vazba: Brožovaná

Vydavatel: Springer-Verlag New York Inc.

Dostupnost: Skladem u dodavatele

Odesíláme za 5-8 dnů

2 286 Kč

Ten years ago Bill Gale of AT&T Bell Laboratories was primary organizer of the first Workshop on Art...

Informace o knize

Autor

Doug Fisher, Hans-J. Lenz

Jazyk

Angličtina

Vazba

Kniha - Brožovaná

Vydáno

1996

Stránek

450

EAN

9780387947365

ISBN

0387947361

Enbook ID

06793798

Vydavatel

Springer-Verlag New York Inc.

Hmotnost

703

Rozměry

155 x 235 x 26

Kompletní popis

Ten years ago Bill Gale of AT&T Bell Laboratories was primary organizer of the first Workshop on Artificial Intelligence and Statistics. In the early days of the Workshop series it seemed clear that researchers in AI and statistics had common interests, though with different emphases, goals, and vocabularies. In learning and model selection, for example, a historical goal of AI to build autonomous agents probably contributed to a focus on parameter-free learning systems, which relied little on an external analyst's assumptions about the data. This seemed at odds with statistical strategy, which stemmed from a view that model selection methods were tools to augment, not replace, the abilities of a human analyst. Thus, statisticians have traditionally spent considerably more time exploiting prior information of the environment to model data and exploratory data analysis methods tailored to their assumptions. In statistics, special emphasis is placed on model checking, making extensive use of residual analysis, because all models are 'wrong', but some are better than others. It is increasingly recognized that AI researchers and/or AI programs can exploit the same kind of statistical strategies to good effect. Often AI researchers and statisticians emphasized different aspects of what in retrospect we might now regard as the same overriding tasks.

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Learning from Data

Artificial Intelligence and Statistics V

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