Advances in Feature Selection for Data and Pattern Recognition, Urszula Sta?czyk; Beata Zielosko; Lakhmi C. Jain
Автор: Urszula Sta?czyk; Beata Zielosko; Lakhmi C. Jain Название: Advances in Feature Selection for Data and Pattern Recognition ISBN: 3319675877 ISBN-13(EAN): 9783319675879 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents recent developments and research trends in the field of feature selection for data and pattern recognition, highlighting a number of recent advances. The field of feature selection is evolving constantly, providing numerous new algorithms, new solutions and new applications.
Автор: Urszula Sta?czyk; Lakhmi C. Jain Название: Feature Selection for Data and Pattern Recognition ISBN: 3662508451 ISBN-13(EAN): 9783662508459 Издательство: Springer Рейтинг: Цена: 18284.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This research book provides the reader with a selection of high-quality texts dedicated to current progress, new developments and research trends in feature selection for data and pattern recognition.
Автор: Urszula Sta?czyk; Lakhmi C. Jain Название: Feature Selection for Data and Pattern Recognition ISBN: 3662456192 ISBN-13(EAN): 9783662456194 Издательство: Springer Рейтинг: Цена: 20896.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This research book provides the reader with a selection of high-quality texts dedicated to current progress, new developments and research trends in feature selection for data and pattern recognition.
Автор: Pablo Duboue Название: The Art of Feature Engineering: Essentials for Machine Learning ISBN: 1108709389 ISBN-13(EAN): 9781108709385 Издательство: Cambridge Academ Рейтинг: Цена: 6970.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This is a guide for data scientists who want to use feature engineering to improve the performance of their machine learning solutions. The book provides a unified view of the field, beginning with basic concepts and techniques, followed by a cross-domain approach to advanced topics, like texts and images, with hands-on case studies.
Автор: Pramod Kumar Pisharady; Prahlad Vadakkepat; Loh Ai Название: Computational Intelligence in Multi-Feature Visual Pattern Recognition ISBN: 9811011710 ISBN-13(EAN): 9789811011719 Издательство: Springer Рейтинг: Цена: 15672.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents a collection of computational intelligence algorithms that addresses issues in visual pattern recognition such as high computational complexity, abundance of pattern features, sensitivity to size and shape variations and poor performance against complex backgrounds.
Автор: Pramod Kumar Pisharady; Prahlad Vadakkepat; Loh Ai Название: Computational Intelligence in Multi-Feature Visual Pattern Recognition ISBN: 9812870555 ISBN-13(EAN): 9789812870551 Издательство: Springer Рейтинг: Цена: 18284.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents a collection of computational intelligence algorithms that addresses issues in visual pattern recognition such as high computational complexity, abundance of pattern features, sensitivity to size and shape variations and poor performance against complex backgrounds.
Автор: Bol?n-Canedo Название: Recent Advances in Ensembles for Feature Selection ISBN: 331990079X ISBN-13(EAN): 9783319900797 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book offers a comprehensive overview of ensemble learning in the field of feature selection (FS), which consists of combining the output of multiple methods to obtain better results than any single method.
Автор: Bradley Efron and Trevor Hastie Название: Computer Age Statistical Inference ISBN: 1107149894 ISBN-13(EAN): 9781107149892 Издательство: Cambridge Academ Рейтинг: Цена: 9029.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.
Автор: Ver?nica Bol?n-Canedo; Noelia S?nchez-Maro?o; Ampa Название: Feature Selection for High-Dimensional Data ISBN: 3319218573 ISBN-13(EAN): 9783319218571 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Introduction to High-Dimensionality.- Foundations of Feature Selection.- Experimental Framework.- Critical Review of Feature Selection Methods.- Application of Feature Selection to Real Problems.- Emerging Challenges.
Автор: Jyotismita Chaki; Nilanjan Dey Название: Texture Feature Extraction Techniques for Image Recognition ISBN: 9811508526 ISBN-13(EAN): 9789811508523 Издательство: Springer Рейтинг: Цена: 7685.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book describes various texture feature extraction approaches and texture analysis applications. It introduces and discusses the importance of texture features, and describes various types of texture features like statistical, structural, signal-processed and model-based.
Автор: Yongzhen Huang; Tieniu Tan Название: Feature Coding for Image Representation and Recognition ISBN: 3662449994 ISBN-13(EAN): 9783662449998 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This brief presents a comprehensive introduction to feature coding, which serves as a key module for the typical object recognition pipeline.
Описание: This book provides a comprehensive introduction to rough set-based feature selection. Rough set theory, first proposed by Zdzislaw Pawlak in 1982, continues to evolve. Concerned with the classification and analysis of imprecise or uncertain information and knowledge, it has become a prominent tool for data analysis, and enables the reader to systematically study all topics in rough set theory (RST) including preliminaries, advanced concepts, and feature selection using RST. The book is supplemented with an RST-based API library that can be used to implement several RST concepts and RST-based feature selection algorithms.The book provides an essential reference guide for students, researchers, and developers working in the areas of feature selection, knowledge discovery, and reasoning with uncertainty, especially those who are working in RST and granular computing. The primary audience of this book is the research community using rough set theory (RST) to perform feature selection (FS) on large-scale datasets in various domains. However, any community interested in feature selection such as medical, banking, and finance can also benefit from the book. This second edition also covers the dominance-based rough set approach and fuzzy rough sets. The dominance-based rough set approach (DRSA) is an extension of the conventional rough set approach and supports the preference order using the dominance principle. In turn, fuzzy rough sets are fuzzy generalizations of rough sets. An API library for the DRSA is also provided with the second edition of the book.
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