Gordon, A.D. Classification 9780367399665

Варианты приобретения

Цена: 65320.00T
Кол-во:
Наличие: Поставка под заказ. Есть в наличии на складе поставщика.
Склад Америка: 170 шт.
При оформлении заказа до: 2025-09-07
Ориентировочная дата поставки: начало Ноября
При условии наличия книги у поставщика.

Добавить в корзину

в Мои желания

Автор: Gordon, A.D.
Название: Classification
ISBN: 9780367399665
Издательство: Taylor&Francis
Классификация:

Вероятность и статистика

ISBN-10: 0367399660
Обложка/Формат: Paperback
Страницы: 268
Вес: 0.50 кг.
Дата издания: 20.12.2019
Серия: Chapman & Hall/CRC Monographs on Statistics and Applied Probability
Язык: English
Издание: 2 ed
Размер: 229 x 152 x 15
Читательская аудитория: Tertiary education (us: college)
Основная тема: Statistical Theory & Methods
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Европейский союз
Описание:

As the amount of information recorded and stored electronically grows ever larger, it becomes increasingly useful, if not essential, to develop better and more efficient ways to summarize and extract information from these large, multivariate data sets. The field of classification does just that-investigates sets of objects to see if they can be summarized into a small number of classes comprising similar objects.
Researchers have made great strides in the field over the last twenty years, and classification is no longer perceived as being concerned solely with exploratory analyses. The second edition of Classification incorporates many of the new and powerful methodologies developed since its first edition. Like its predecessor, this edition describes both clustering and graphical methods of representing data, and offers advice on how to decide which methods of analysis best apply to a particular data set. It goes even further, however, by providing critical overviews of recent developments not widely known, including efficient clustering algorithms, cluster validation, consensus classifications, and the classification of symbolic data.
The author has taken an approach accessible to researchers in the wide variety of disciplines that can benefit from classification analysis and methods. He illustrates the methodologies by applying them to data sets-smaller sets given in the text, larger ones available through a Web site.
Large multivariate data sets can be difficult to comprehend-the sheer volume and complexity can prove overwhelming. Classification methods provide efficient, accurate ways to make them less unwieldy and extract more information. Classification, Second Edition offers the ideal vehicle for gaining the background and learning the methodologies-and begin putting these techniques to use.

Classification, Gordon, A.D.