Face Image Analysis by Unsupervised Learning, Marian Stewart Bartlett
Автор: Yang Yun Название: Temporal Data Mining via Unsupervised Ensemble Learning ISBN: 0128116544 ISBN-13(EAN): 9780128116548 Издательство: Elsevier Science Рейтинг: Цена: 7241.00 р. Наличие на складе: Поставка под заказ.
Описание: Temporal Data Mining via Unsupervised Ensemble Learning provides the principle knowledge of temporal data mining in association with unsupervised ensemble learning and the fundamental problems of temporal data clustering from different perspectives. By providing three proposed ensemble approaches of temporal data clustering, this book presents a practical focus of fundamental knowledge and techniques, along with a rich blend of theory and practice. . Furthermore, the book includes illustrations of the proposed approaches based on data and simulation experiments to demonstrate all methodologies, and is a guide to the proper usage of these methods. As there is nothing universal that can solve all problems, it is important to understand the characteristics of both clustering algorithms and the target temporal data so the correct approach can be selected for a given clustering problem. . Scientists, researchers, and data analysts working with machine learning and data mining will benefit from this innovative book, as will undergraduate and graduate students following courses in computer science, engineering, and statistics.
Автор: Bruno Baruque Название: Fusion Methods for Unsupervised Learning Ensembles ISBN: 3642423280 ISBN-13(EAN): 9783642423284 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book examines the potential of the ensemble meta-algorithm by describing and testing a technique based on the combination of ensembles and statistical PCA that is able to determine the presence of outliers in high-dimensional data sets.
Автор: Oliver Kramer Название: Dimensionality Reduction with Unsupervised Nearest Neighbors ISBN: 3642386512 ISBN-13(EAN): 9783642386510 Издательство: Springer Рейтинг: Цена: 19591.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is devoted to a novel approach for dimensionality reduction based on the famous nearest neighbor method that is a powerful classification and regression approach.
Описание: Expanding upon presentations at last year`s SUEMA (Supervised and Unsupervised Ensemble Methods and Applications) meeting, this volume explores recent developments in the field. Useful examples act as a guide for practitioners in computational intelligence.
This book constitutes the refereed joint proceedings of the Third International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2017, and the 6th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Quebec City, QC, Canada, in September 2017.
The 38 full papers presented at DLMIA 2017 and the 5 full papers presented at ML-CDS 2017 were carefully reviewed and selected. The DLMIA papers focus on the design and use of deep learning methods in medical imaging. The ML-CDS papers discuss new techniques of multimodal mining/retrieval and their use in clinical decision support.
Автор: Yefeng Zheng; Dorin Comaniciu Название: Marginal Space Learning for Medical Image Analysis ISBN: 1493955756 ISBN-13(EAN): 9781493955756 Издательство: Springer Рейтинг: Цена: 11179.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Automatic detection and segmentation of anatomical structures in medical images are prerequisites to subsequent image measurements and disease quantification, and therefore have multiple clinical applications.
Автор: Sanghamitra Bandyopadhyay; Sriparna Saha Название: Unsupervised Classification ISBN: 3642428363 ISBN-13(EAN): 9783642428364 Издательство: Springer Рейтинг: Цена: 6981.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book offers a theoretical analysis of symmetry-based clustering techniques. It includes extensive real-world applications in data mining, remote sensing imaging, MR brain imaging, gene expression data analysis, and face detection.
Автор: Zheng Название: Marginal Space Learning for Medical Image Analysis ISBN: 1493905996 ISBN-13(EAN): 9781493905997 Издательство: Springer Рейтинг: Цена: 11179.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Automatic detection and segmentation of anatomical structures in medical images are prerequisites to subsequent image measurements and disease quantification, and therefore have multiple clinical applications.
Описание: Ensembles of Clustering Methods and Their Applications.- Cluster Ensemble Methods: from Single Clusterings to Combined Solutions.- Random Subspace Ensembles for Clustering Categorical Data.- Ensemble Clustering with a Fuzzy Approach.- Collaborative Multi-Strategical Clustering for Object-Oriented Image Analysis.- Ensembles of Classification Methods and Their Applications.- Intrusion Detection in Computer Systems Using Multiple Classifier Systems.- Ensembles of Nearest Neighbors for Gene Expression Based Cancer Classification.- Multivariate Time Series Classification via Stacking of Univariate Classifiers.- Gradient Boosting GARCH and Neural Networks for Time Series Prediction.- Cascading with VDM and Binary Decision Trees for Nominal Data.- Erratum.
Автор: Oliver Kramer Название: Dimensionality Reduction with Unsupervised Nearest Neighbors ISBN: 3662518953 ISBN-13(EAN): 9783662518953 Издательство: Springer Рейтинг: Цена: 16977.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is devoted to a novel approach for dimensionality reduction based on the famous nearest neighbor method that is a powerful classification and regression approach.
Описание: This textbook is an overview of theories, methodologies, and recent developments in the field, covering the theoretical foundation and providing a complete summary of the latest advances. It also presents key issues to be considered in making a real system.
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