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Classification in the Wild: The Art and Science of Transparent Decision Making

(Hardback)


Publishing Details

Full Title:

Classification in the Wild: The Art and Science of Transparent Decision Making

Contributors:

By (Author) Konstantinos Katsikopoulos
By (author) Ozgur Simsek

ISBN:

9780262045155

Publisher:

MIT Press Ltd

Imprint:

MIT Press

Publication Date:

4th May 2021

Country:

United States

Classifications

Readership:

General

Fiction/Non-fiction:

Non Fiction

Dewey:

121.4

Physical Properties

Physical Format:

Hardback

Number of Pages:

200

Dimensions:

Width 152mm, Height 229mm

Description

Rules for building formal models that use fast-and-frugal heuristics, extending the psychological study of classification to the real world of uncertainty. This book focuses on classification--allocating objects into categories--"in the wild," in real-world situations and far from the certainty of the lab. In the wild, unlike in typical psychological experiments, the future is not knowable and uncertainty cannot be meaningfully reduced to probability. Connecting the science of heuristics with machine learning, the book shows how to create formal models using classification rules that are simple, fast, and transparent and that can be as accurate as mathematically sophisticated algorithms developed for machine learning.

Author Bio

Konstantinos Katsikopoulos is Associate Professor (Reader) of Behavioural Operations at the Southampton Business School, where he is also Head of Research in the Department of Decision Analytics and Risk. Ozgur Simsek is Senior Lecturer in Machine Learning in the Department of Computer Science at the University of Bath, where he is also Deputy Director of the Institute for Mathematical Innovation. Marcus Buckmann is Senior Data Research Analyst at the Advanced Analytics Division of the Bank of England. Gerd Gigerenzer is Director of the Harding Center for Risk Literacy at the Max Planck Institute for Human Development in Berlin and Partner in Simply Rational--The Institute for Decisions.

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