Metalearning : applications to automated machine learning and data mining | Kementerian Pendidikan Dasar dan Menengah

Search by :

ALL Author Subject ISBN/ISSN Advanced Search

Last search:

Image of Metalearning : applications to automated machine learning and data mining

Text

Metalearning : applications to automated machine learning and data mining

Brazdil, Pavel - Personal Name; van Rijn, Jan N. - Personal Name; Soares, Carlos - Personal Name; Vanschoren, Joaquin - Personal Name;

This open access book offers a comprehensive and thorough introduction to almost all aspects of metalearning and automated machine learning (AutoML), covering the basic concepts and architecture, evaluation, datasets, hyperparameter optimization, ensembles and workflows, and also how this knowledge can be used to select, combine, compose, adapt and configure both algorithms and models to yield faster and better solutions to data mining and data science problems. It can thus help developers to develop systems that can improve themselves through experience.

As one of the fastest-growing areas of research in machine learning, metalearning studies principled methods to obtain efficient models and solutions by adapting machine learning and data mining processes. This adaptation usually exploits information from past experience on other tasks and the adaptive processes can involve machine learning approaches. As a related area to metalearning and a hot topic currently, AutoML is concerned with automating the machine learning processes. Metalearning and AutoML can help AI learn to control the application of different learning methods and acquire new solutions faster without unnecessary interventions from the user.

This book is a substantial update of the first edition published in 2009. It includes 18 chapters, more than twice as much as the previous version. This enabled the authors to cover the most relevant topics in more depth and incorporate the overview of recent research in the respective area. The book will be of interest to researchers and graduate students in the areas of machine learning, data mining, data science and artificial intelligence.

Availability

No copy data

Detail Information

Series Title: -
Call Number: 006.31 MET m
Publisher: Cham, Switzerland : Springer Open., 2022
Collation: xii, 346p. : ill,
Language: English
ISBN/ISSN: 9783030670245
Classification: 006.31
Content Type: -
Media Type: -
Carrier Type: -
Edition: Second Edition
Subject(s): Artificial intelligence
Computer Science
Data mining
Machine learning
Optical pattern recognition
Specific Detail Info: -
Statement of Responsibility: Pavel Brazdil [et. al.]

Other version/related

No other version available

File Attachment

9783030670245
https://link.springer.com/book/10.1007/978-3-030-67024-5
Other Resource Link

Comments

You must be logged in to post a comment