Cost-sensitive machine learning
by Krishnapuram, Balaji Rao, Bharat Yu, Shipeng
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 researc…
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- Full title :Cost-sensitive machine learning / edited by Balaji Krishnapuram, Shipeng Yu, Bharat Rao.
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.
Read More ↓Edition Statements
- Publication Date:©2012.
Publication Statements
- Publisher(s):CRC Press
- Place of Publication:Boca Raton, FL
- Language:eng
- Publication Date:©2012.
The Physical Object
- Description:1 online resource : : illustrations
Edition Identifiers
- ISBN:9781439839287, 143983928X, 9781466548176, 1466548177
- oclc:ocn785416992
- LC Classification:Q325.5
- Dewey Decimal:006.31
Table of Contents
pt. 1. Theoretical underpinnings of cost-sensitive machine learning -- pt. 2. Cost-sensitive machine learning applications.
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Cost-sensitive machine learning. Bharat Rao, Ship…
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