Optimum-Path Forest: Theory, Algorithms, and Applications

The Optimum-Path Forest (OPF) classifier was first published in 2008 and has since expanded to various applications, including multi-label and semi-supervised versions. The book provides an overview of the principles, algorithms, and applications of OPF, covering theory, state-of-the-art, and future directions.

Format: Paperback / softback
Length: 244 pages
Publication date: 24 January 2022
Publisher: Elsevier Science Publishing Co Inc

The Optimum-Path Forest (OPF) classifier, a groundbreaking innovation in the field of machine learning, made its debut in 2008. This remarkable classifier was initially introduced in both supervised and unsupervised versions, with applications spanning medicine and image classification. Since then, its scope has expanded exponentially, encompassing a wide range of diverse fields such as remote sensing, electrical and petroleum engineering, and biology. In recent years, the development of multi-label and semi-supervised versions has further enriched its capabilities, making it adept at handling complex video classification tasks.

This comprehensive book serves as a valuable resource, providing a comprehensive exploration of the principles, algorithms, and applications of Optimum-Path Forest. It delves into the theoretical foundations, presenting the state-of-the-art techniques and insights into the field's future directions. By offering a comprehensive overview, the book equips readers with a deep understanding of this powerful classifier and its potential applications across a multitude of industries.

The Optimum-Path Forest (OPF) classifier has revolutionized the landscape of machine learning, offering a robust and versatile solution for a wide range of classification tasks. Its adaptability and efficiency have made it a staple in the field, and its continued development promises to lead to even more exciting advancements in the years to come. Whether you are a researcher, practitioner, or simply interested in exploring the latest developments in machine learning, this book is an essential read for anyone seeking to stay at the forefront of this rapidly evolving field.

Weight: 400g
Dimension: 152 x 229 x 15 (mm)
ISBN-13: 9780128226889