Asset Details
Do you wish to reserve the book?
Ensemble Machine Learning: Advances in Research and Applications
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Ensemble Machine Learning: Advances in Research and Applications
Do you wish to request the book?
Ensemble Machine Learning: Advances in Research and Applications
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
eBook
Ensemble Machine Learning: Advances in Research and Applications
2024
Overview
This book delves into the dynamic realm of ensemble methods, offering a comprehensive exploration of its evolution, methodologies, and diverse applications. Chapters are gathered from the collective wisdom of researchers, practitioners, and innovators who have pioneered this ever-evolving domain. This book serves as a compendium, bringing together theoretical foundations, cutting-edge advancements, and practical insights, catering to both seasoned experts and those venturing into the intricate world of ensemble learning. Each chapter encapsulates the essence of collaboration among diverse models, unveiling the intricacies of ensemble techniques, their fusion strategies, and their impact across industries. From boosting algorithms to bagging, stacking, and beyond, this book illuminates the nuances of ensemble learning, illustrating how these techniques amplify predictive accuracy, enhance generalization, and fortify models against the complexities of real-world data. The editors hope this book will serve as a guiding beacon for enthusiasts, researchers, and practitioners navigating the intricate landscape of ensemble machine learning, fostering innovation, and paving the way for future breakthroughs.
Publisher
Nova
ISBN
9798895300046
We currently cannot retrieve any items related to this title. Kindly check back at a later time.