Recent Advances in Ensembles for Feature Selection, Bolуn-Canedo Verуnica, Alonso-Betanzos Amparo
Автор: Aggarwal Charu C., Sathe Saket Название: Outlier Ensembles: An Introduction ISBN: 3319854747 ISBN-13(EAN): 9783319854748 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book discusses a variety of methods for outlier ensembles and organizes them by the specific principles with which accuracy improvements are achieved. The authors cover how outlier ensembles relate (both theoretically and practically) to the ensemble techniques used commonly for other data mining problems like classification.
Описание: This book focuses on the fields of hybrid intelligent systems based on fuzzy systems, neural networks, bio-inspired algorithms and time series. Prediction errors are evaluated by the following metrics: Mean Absolute Error, Mean Square Error, Root Mean Square Error, Mean Percentage Error and Mean Absolute Percentage Error.
Автор: Charu C. Aggarwal; Saket Sathe Название: Outlier Ensembles ISBN: 331954764X ISBN-13(EAN): 9783319547640 Издательство: Springer Рейтинг: Цена: 10480.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book discusses a variety of methods for outlier ensembles and organizes them by the specific principles with which accuracy improvements are achieved. The authors cover how outlier ensembles relate (both theoretically and practically) to the ensemble techniques used commonly for other data mining problems like classification.
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.
Introduction to Feature Selection.- Background.- Rough Set Theory.- Advance Concepts in RST.- Rough Set Based Feature Selection Techniques.- Unsupervised Feature Selection using RST.- Critical Analysis of Feature Selection Algorithms.- RST Source Code.
Описание: This book provides a comprehensive introduction to rough set-based feature selection. 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.
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: Oleg Okun; Giorgio Valentini; Matteo Re Название: Ensembles in Machine Learning Applications ISBN: 3662507064 ISBN-13(EAN): 9783662507063 Издательство: Springer Рейтинг: Цена: 16977.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book collects papers from the 3rd Workshop on Supervised and Unsupervised Ensemble Methods and their Applications (SUEMA), held as part of the 2010 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases.
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: 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; Beata Zielosko; Lakhmi C. Jain Название: Advances in Feature Selection for Data and Pattern Recognition ISBN: 3319884522 ISBN-13(EAN): 9783319884523 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: 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 latest advances.
The field of feature selection is evolving constantly, providing numerous new algorithms, new solutions, and new applications. Some of the advances presented focus on theoretical approaches, introducing novel propositions highlighting and discussing properties of objects, and analysing the intricacies of processes and bounds on computational complexity, while others are dedicated to the specific requirements of application domains or the particularities of tasks waiting to be solved or improved.
Divided into four parts – nature and representation of data; ranking and exploration of features; image, shape, motion, and audio detection and recognition; decision support systems, it is of great interest to a large section of researchers including students, professors and practitioners.
Автор: Athanasios Voulodimos, Anastasios Doulamis Название: Recent Advances in 3D Imaging, Modeling, and Reconstruction ISBN: 1799829960 ISBN-13(EAN): 9781799829966 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 20236.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 3D image reconstruction is used in many fields, such as medicine, entertainment, and computer science. This highly demanded process comes with many challenges, such as images becoming blurry by atmospheric turbulence, getting snowed with noise, or becoming damaged within foreign regions. It is imperative to remain well-informed with the latest research in this field.
Recent Advances in 3D Imaging, Modeling, and Reconstruction is a collection of innovative research on the methods and common techniques of image reconstruction as well as the accuracy of these methods. Featuring coverage on a wide range of topics such as ray casting, holographic techniques, and machine learning, this publication is ideally designed for graphic designers, computer engineers, medical professionals, robotics engineers, city planners, game developers, researchers, academicians, and students.
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