Imbalanced Learning

Foundations, Algorithms, and Applications

de

,

Éditeur :

Wiley-IEEE Press


Paru le : 2013-06-07



eBook Téléchargement , DRM LCP 🛈 DRM Adobe 🛈
Lecture en ligne (streaming)
136,04

Téléchargement immédiat
Dès validation de votre commande
Ajouter à ma liste d'envies
Image Louise Reader présentation

Louise Reader

Lisez ce titre sur l'application Louise Reader.

Description

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 learning
Imbalanced 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 Learning Imbalanced Datasets: From Sampling to Classifiers Ensemble Methods for Class Imbalance Learning Class Imbalance Learning Methods for Support Vector Machines Class Imbalance and Active Learning Nonstationary Stream Data Learning with Imbalanced Class Distribution Assessment Metrics for Imbalanced Learning
Imbalanced 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.
Pages
224 pages
Collection
n.c
Parution
2013-06-07
Marque
Wiley-IEEE Press
EAN papier
9781118074626
EAN PDF
9781118646205

Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
224
Taille du fichier
2632 Ko
Prix
136,04 €
EAN EPUB
9781118646335

Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
224
Taille du fichier
5673 Ko
Prix
136,04 €

Suggestions personnalisées