1.

Record Nr.

UNINA9910918598403321

Autore

Chakraborty Sanjay

Titolo

Multi-objective, Multi-class and Multi-label Data Classification with Class Imbalance : Theory and Practices / / by Sanjay Chakraborty, Lopamudra Dey

Pubbl/distr/stampa

Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024

ISBN

9789819796229

9789819796212

Edizione

[1st ed. 2024.]

Descrizione fisica

1 online resource (177 pages)

Collana

Springer Tracts in Nature-Inspired Computing, , 2524-5538

Altri autori (Persone)

DeyLopamudra

Disciplina

006.3

Soggetti

Computational intelligence

Artificial intelligence

Machine learning

Computational Intelligence

Artificial Intelligence

Machine Learning

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

1. Introduction to Classification -- 2. Class Imbalance and Data Irregularities in Classification -- 3. Multi-class Classification -- 4. Multi-Objective and Multi-Label Classification -- 5. Deep Learning Inspired Multiclass and Multilabel Classification -- 6. Applications of Multi-objective, Multi-label and Multi-class Classifications.

Sommario/riassunto

This book explores intricate world of data classification with 'Multi-Objective, Multi-Class, and Multi-Label Data Classification.' This book studies sophisticated methods and strategies for working with complicated data sets, tackling the difficulties of various classes, many objectives, and complicated labelling tasks. This resource fosters a deeper grasp of multi-dimensional data analysis in today's data-driven world by providing readers with the skills and insights needed to navigate the subtleties of modern classification jobs, from algorithmic techniques to practical applications.