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Sampling Techniques for Supervised or Unsupervised Tasks

Sampling Techniques for Supervised or Unsupervised Tasks

Paperback

Series: Unsupervised and Semi-Supervised Learning

Technology & EngineeringDatabases

ISBN10: 3030293513
ISBN13: 9783030293512
Publisher: Springer Nature
Published: Nov 21 2020
Pages: 232
Weight: 0.78
Height: 0.52 Width: 6.14 Depth: 9.21
Language: English

This book describes in detail sampling techniques that can be used for unsupervised and supervised cases, with a focus on sampling techniques for machine learning algorithms. It covers theory and models of sampling methods for managing scalability and the curse of dimensionality, their implementations, evaluations, and applications. A large part of the book is dedicated to database comprising standard feature vectors, and a special section is reserved to the handling of more complex objects and dynamic scenarios. The book is ideal for anyone teaching or learning pattern recognition and interesting teaching or learning pattern recognition and is interested in the big data challenge. It provides an accessible introduction to the field and discusses the state of the art concerning sampling techniques for supervised and unsupervised task.

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