Imbalanced Learning: Foundations, Algorithms, and Applications Haibo He

ISBN: 9781118074626

Published: July 1st 2013

Hardcover

210 pages


Description

Imbalanced Learning: Foundations, Algorithms, and Applications  by  Haibo He

Imbalanced Learning: Foundations, Algorithms, and Applications by Haibo He
July 1st 2013 | Hardcover | PDF, EPUB, FB2, DjVu, AUDIO, mp3, ZIP | 210 pages | ISBN: 9781118074626 | 9.11 Mb

The first book of its kind to review the current status and future direction of the exciting new branch of machine learning/data mining called imbalanced learningImbalanced learning focuses on how an intelligent system can learn when it is providedMoreThe first book of its kind to review the current status and future direction of the exciting new branch of machine learning/data mining called imbalanced learningImbalanced learning focuses on how an intelligent system can learn when it is provided with imbalanced data.

Solving imbalanced learning problems is critical in numerous data-intensive networked systems, including surveillance, security, Internet, finance, biomedical, defense, and more. Due to the inherent complex characteristics of imbalanced data sets, learning from such data requires new understandings, principles, algorithms, and tools to transform vast amounts of raw data efficiently into information and knowledge representation.The first comprehensive look at this new branch of machine learning, this book offers a critical review of the problem of imbalanced learning, covering the state of the art in techniques, principles, and real-world applications.

Featuring contributions from experts in both academia and industry, Imbalanced Learning: Foundations, Algorithms, and Applications provides chapter coverage on: Foundations of Imbalanced LearningImbalanced Datasets: From Sampling to ClassifiersEnsemble Methods for Class Imbalance LearningClass Imbalance Learning Methods for Support Vector MachinesClass Imbalance and Active LearningNonstationary Stream Data Learning with Imbalanced Class DistributionAssessment Metrics for Imbalanced LearningImbalanced Learning: Foundations, Algorithms, and Applications will help scientists and engineers learn how to tackle the problem of learning from imbalanced datasets, and gain insight into current developments in the field as well as future research directions.



Enter the sum





Related Archive Books



Related Books


Comments

Comments for "Imbalanced Learning: Foundations, Algorithms, and Applications":


lifeandtimesofchantel.com

©2014-2015 | DMCA | Contact us