Cost-Sensitive Machine Learning -  - Bücher - Taylor & Francis Ltd - 9780367381912 - 19. September 2019
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Cost-Sensitive Machine Learning 1. Ausgabe

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In machine learning applications, practitioners must take into account the cost associated with the algorithm. These costs include:







Cost of acquiring training data



Cost of data annotation/labeling and cleaning

Computational cost for model fitting, validation, and testing

Cost of collecting features/attributes for test data

Cost of user feedback collection

Cost of incorrect prediction/classification



Cost-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 of learning into the modeling process.





The first part of the book presents the theoretical underpinnings of cost-sensitive machine learning. It describes well-established machine learning approaches for reducing data acquisition costs during training as well as approaches for reducing costs when systems must make predictions for new samples. The second part covers real-world applications that effectively trade off different types of costs. These applications not only use traditional machine learning approaches, but they also incorporate cutting-edge research that advances beyond the constraining assumptions by analyzing the application needs from first principles.





Spurring further research on several open problems, this volume highlights the often implicit assumptions in machine learning techniques that were not fully understood in the past. The book also illustrates the commercial importance of cost-sensitive machine learning through its coverage of the rapid application developments made by leading companies and academic research labs.


331 pages

Medien Bücher     Taschenbuch   (Buch mit Softcover und geklebtem Rücken)
Erscheinungsdatum 19. September 2019
ISBN13 9780367381912
Verlag Taylor & Francis Ltd
Seitenanzahl 331
Maße 150 × 220 × 10 mm   ·   453 g
Sprache Englisch  
Redakteur Krishnapuram, Balaji
Redakteur Rao, R. Bharat
Redakteur Yu, Shipeng

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