Feature Selection for High-Dimensional Data, Ver?nica Bol?n-Canedo; Noelia S?nchez-Maro?o; Ampa
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: Basant Agarwal; Namita Mittal Название: Prominent Feature Extraction for Sentiment Analysis ISBN: 3319253417 ISBN-13(EAN): 9783319253411 Издательство: Springer Рейтинг: Цена: 18284.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
1 Introduction
2 Literature Survey
3 Machine Learning Approach for Sentiment Analysis
4 Semantic Parsing using Dependency Rules
5 Sentiment Analysis using ConceptNet Ontology and Context
Information
6 Semantic Orientation based Approach for Sentiment Analysis
7 Conclusions and FutureWork
References
Glossary Index
Автор: Francesco Masulli; Alfredo Petrosino; Stefano Rove Название: Clustering High--Dimensional Data ISBN: 3662485761 ISBN-13(EAN): 9783662485767 Издательство: Springer Рейтинг: Цена: 5590.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the proceedings of the International Workshop on Clustering High-Dimensional Data, CHDD 2012, held in Naples, Italy, in May 2012. and the most common approach to tackle dimensionality problems, namely, dimensionality reduction and its application in clustering.
Описание: After exploring the inherent structures of the visual data, it proposes a number of computational models covering an extensive range of mathematical topics, including compressive sensing, graph theory, probabilistic learning and information theory.
Описание: After exploring the inherent structures of the visual data, it proposes a number of computational models covering an extensive range of mathematical topics, including compressive sensing, graph theory, probabilistic learning and information theory.
Автор: Huan Liu; Hiroshi Motoda Название: Instance Selection and Construction for Data Mining ISBN: 1441948619 ISBN-13(EAN): 9781441948618 Издательство: Springer Рейтинг: Цена: 27245.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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