Feature and Dimensionality Reduction for Clustering with Deep Learning

Discover the cutting-edge techniques in data analysis with Feature and Dimensionality Reduction for Clustering with Deep Learning by Frederic Ros. Published in 2024 by Springer International Publishing AG, this hardback edition spans 268 pages and offers an insightful overview of the latest methods in feature selection and dimensionality reduction. The book focuses on the application of Deep Neural Networks (DNNs) within the realm of clustering, addressing critical questions in knowledge discovery. Perfect for researchers and practitioners alike, this comprehensive guide delves into innovative strategies that enhance clustering performance through advanced deep learning techniques. Equip yourself with the knowledge to navigate the complexities of data clustering and elevate your analytical skills with this essential resource.