Cost-sensitive machine learning

In machine learning applications, practitioners must take into account the cost associated with the algorithm. These costs include: Cost of acquiring training dataCost of data annotation/labeling and cleaningComputational cost for model fitting, validation, and testingCost of collecting features/att...

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Bibliographic Details
Main Author: Krishnapuram, Balaji
Other Authors: Yu, Shipeng, Rao, Bharat
Format: eBook
Language:English
Published: Boca Raton, FL CRC Press 2012
Series:Chapman & Hall/CRC machine learning & pattern recognition series
Subjects:
Online Access:
Collection: O'Reilly - Collection details see MPG.ReNa
Description
Summary:In machine learning applications, practitioners must take into account the cost associated with the algorithm. These costs include: Cost of acquiring training dataCost of data annotation/labeling and cleaningComputational cost for model fitting, validation, and testingCost of collecting features/attributes for test dataCost of user feedback collectionCost of incorrect prediction/classificationCost-Sensitive Machine Learning is one of the first books to provide an overview of the current research efforts and problems in this area. It discusses real-world applications that incorporate the cost o
Physical Description:1 online resource illustrations
ISBN:9781466548176
9781439839287
143983928X