£108.01

Springer Improving Classifier Generalization - Vol 989 Book

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Description

Explore advanced concepts in machine learning with Improving Classifier Generalization: Real-Time Machine Learning based Applications. Published by Springer as part of the Studies in Computational Intelligence series (Volume 989), this technical book addresses the specific challenges of classifier generalization in real-time environments. This volume serves as a specialized resource for professionals and researchers working within the fields of computer science, artificial intelligence, and machine learning. It focuses on the practical application of machine learning models to ensure they perform effectively when faced with real-time data streams. By studying the methodologies presented in this series, readers can better understand how to improve the reliability and accuracy of automated classification systems. Whether you are studying computational intelligence or applying AI to complex computing tasks, this Springer publication provides the necessary academic foundation for mastering modern machine learning applications.

Key Features

Part of the Studies in Computational Intelligence series, providing a recognized academic framework for researchers.

Focuses on real-time machine learning applications to help address modern computing challenges.

Covers essential topics regarding classifier generalization for improved model performance.

Published by Springer, a leading name in scientific and technical literature.

Volume 989 offers specialized knowledge for computer science and AI professionals.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
02 October 2023
Listed Since
03 September 2023

Barcode

No barcode data available

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