Learning from Data Streams, Jo?o Gama; Mohamed Medhat Gaber
Автор: Moamar Sayed-Mouchaweh Название: Learning from Data Streams in Dynamic Environments ISBN: 3319256653 ISBN-13(EAN): 9783319256658 Издательство: Springer Рейтинг: Цена: 9141.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Also presents the problem of learning in non-stationary environments, its interests, its applications and challenges and studies the complementarities and the links between the different methods and techniques of learning in evolving and non-stationary environments.
Описание: Constitutes the refereed proceedings of the 7th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2009, held in Tubingen, Germany, in April 2009 co located with the Evo 2009 events. This book includes such topics as biomarker discovery, cell simulation and modeling, and ecological modeling.
Автор: Bertrand Clarke; Ernest Fokoue; Hao Helen Zhang Название: Principles and Theory for Data Mining and Machine Learning ISBN: 1461417074 ISBN-13(EAN): 9781461417071 Издательство: Springer Рейтинг: Цена: 21661.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a thorough introduction to the most important topics in data mining and machine learning. All the topics covered have undergone rapid development and this treatment offers a modern perspective emphasizing the most recent contributions.
Автор: Shi Yu; L?on-Charles Tranchevent; Bart Moor; Yves Название: Kernel-based Data Fusion for Machine Learning ISBN: 3642267513 ISBN-13(EAN): 9783642267512 Издательство: Springer Рейтинг: Цена: 19589.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Data fusion problems arise in many different fields. This book provides a specific introduction to solve data fusion problems using support vector machines. The reader will require a good knowledge of data mining, machine learning and linear algebra.
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: Pardalos Название: Machine Learning, Optimization, and Big Data ISBN: 3319514687 ISBN-13(EAN): 9783319514680 Издательство: Springer Рейтинг: Цена: 9224.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes revised selected papers from the Second International Workshop on Machine Learning, Optimization, and Big Data, MOD 2016, held in Volterra, Italy, in August 2016. The 40 papers presented in this volume were carefully reviewed and selected from 97 submissions.
Описание: This book constitutes the refereed proceedings of the 17 International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2016, held in Yangzhou, China, in October 2016. The 68 full papers presented were carefully reviewed and selected from 115 submissions. They provide a valuable and timely sample of latest research outcomes in data engineering and automated learning ranging from methodologies, frameworks, and techniques to applications including various topics such as evolutionary algorithms; deep learning; neural networks; probabilistic modeling; particle swarm intelligence; big data analysis; applications in regression, classification, clustering, medical and biological modeling and predication; text processing and image analysis.
Автор: Douzal-Chouakria Название: Advanced Analysis and Learning on Temporal Data ISBN: 3319444115 ISBN-13(EAN): 9783319444116 Издательство: Springer Рейтинг: Цена: 5870.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The last part of the book is dedicated to metric learning and time series comparison, it addresses the problem of speeding-up the dynamic time warping or dealing with multi-modal and multi-scale metric learning for time series classification and clustering.
Автор: Carneiro Название: Deep Learning and Data Labeling for Medical Applications ISBN: 3319469754 ISBN-13(EAN): 9783319469751 Издательство: Springer Рейтинг: Цена: 6988.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereed proceedings of two workshops held at the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, in Athens, Greece, in October 2016: the First Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2016, and the Second International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2016. The 28 revised regular papers presented in this book were carefully reviewed and selected from a total of 52 submissions. The 7 papers selected for LABELS deal with topics from the following fields: crowd-sourcing methods; active learning; transfer learning; semi-supervised learning; and modeling of label uncertainty.
The 21 papers selected for DLMIA span a wide range of topics such as image description; medical imaging-based diagnosis; medical signal-based diagnosis; medical image reconstruction and model selection using deep learning techniques; meta-heuristic techniques for fine-tuning parameter in deep learning-based architectures; and applications based on deep learning techniques.
Автор: Perner Название: Machine Learning and Data Mining in Pattern Recognition ISBN: 3319419196 ISBN-13(EAN): 9783319419190 Издательство: Springer Рейтинг: Цена: 13416.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining.
Автор: Hujun Yin; Yang Gao; Songcan Chen; Yimin Wen; Guoy Название: Intelligent Data Engineering and Automated Learning – IDEAL 2017 ISBN: 3319689347 ISBN-13(EAN): 9783319689340 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereed proceedings of the 18th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2017, held in Guilin, China, in October/November 2017. The 65 full papers presented were carefully reviewed and selected from 110 submissions.
Автор: Alexander Mehler; Kai-Uwe K?hnberger; Henning Lobi Название: Modeling, Learning, and Processing of Text-Technological Data Structures ISBN: 3642269443 ISBN-13(EAN): 9783642269448 Издательство: Springer Рейтинг: Цена: 23508.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Researchers in many disciplines have been concerned with modeling textual data in order to account for texts as the primary information unit of written communication.
ООО "Логосфера " Тел:+7(495) 980-12-10 www.logobook.ru
