Big Data Analysis: New Algorithms for a New Society, Nathalie Japkowicz; Jerzy Stefanowski

Автор: B. S.P. Mishra; Satchidananda Dehuri; Euiwhan Kim;
Название: Techniques and Environments for Big Data Analysis
ISBN: 3319275186 ISBN-13(EAN): 9783319275185
Издательство: Springer
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Цена: 113190.00 T
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Описание: This volume is aiming at a wide range of readers andresearchers in the area of Big Data by presenting the recent advances in the fieldsof Big Data Analysis, as well as the techniques and tools used to analyze it.

Автор: Javier Esparza; Rupak Majumdar
Название: Tools and Algorithms for the Construction and Analysis of Systems
ISBN: 3642120016 ISBN-13(EAN): 9783642120015
Издательство: Springer
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Цена: 83850.00 T
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Описание: Constitutes the refereed proceedings of the 16th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2010, held in Paphos, Cyprus, in March 2010, as part of ETAPS 2010, the European Joint Conferences on Theory and Practice of Software.

Автор: Xiangyu Kong; Changhua Hu; Zhansheng Duan
Название: Principal and Minor Component Analysis Neural Networks to Principal Component Analysis Networks and Algorithms
ISBN: 981102913X ISBN-13(EAN): 9789811029134
Издательство: Springer
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Цена: 139750.00 T
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Описание: This book not only provides a comprehensive introduction to neural-based PCA methods in control science, but also presents many novel PCA algorithms and their extensions and generalizations, e.g., dual purpose, coupled PCA, GED, neural based SVD algorithms, etc.

Автор: Slawomir Wierzcho?; Mieczyslaw A. K?opotek
Название: Modern Algorithms of Cluster Analysis
ISBN: 3319693077 ISBN-13(EAN): 9783319693071
Издательство: Springer
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Цена: 149060.00 T
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Описание: This book provides the reader with a basic understanding of the formal concepts of the cluster, clustering, partition, cluster analysis etc. The book explains feature-based, graph-based and spectral clustering methods and discusses their formal similarities and differences. Understanding the related formal concepts is particularly vital in the epoch of Big Data; due to the volume and characteristics of the data, it is no longer feasible to predominantly rely on merely viewing the data when facing a clustering problem. Usually clustering involves choosing similar objects and grouping them together. To facilitate the choice of similarity measures for complex and big data, various measures of object similarity, based on quantitative (like numerical measurement results) and qualitative features (like text), as well as combinations of the two, are described, as well as graph-based similarity measures for (hyper) linked objects and measures for multilayered graphs. Numerous variants demonstrating how such similarity measures can be exploited when defining clustering cost functions are also presented. In addition, the book provides an overview of approaches to handling large collections of objects in a reasonable time. In particular, it addresses grid-based methods, sampling methods, parallelization via Map-Reduce, usage of tree-structures, random projections and various heuristic approaches, especially those used for community detection.

Автор: Shan Suthaharan
Название: Machine Learning Models and Algorithms for Big Data Classification
ISBN: 1489978526 ISBN-13(EAN): 9781489978523
Издательство: Springer
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Цена: 121110.00 T
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Описание: This book presents machine learning models and algorithms to address big data classification problems. The first part mainly focuses on the topics that are needed to help analyze and understand data and big data. The third part presents the topics required to understand and select machine learning techniques to classify big data.

Автор: D.P. Acharjya; Satchidananda Dehuri; Sugata Sanyal
Название: Computational Intelligence for Big Data Analysis
ISBN: 3319165976 ISBN-13(EAN): 9783319165974
Издательство: Springer
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Цена: 121890.00 T
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Описание: The work presented in this book is a combination of theoretical advancements of big data analysis, cloud computing, and their potential applications in scientific computing. The book discusses major issues pertaining to big data analysis using computational intelligence techniques and some issues of cloud computing.

Автор: D.P. Acharjya; Satchidananda Dehuri; Sugata Sanyal
Название: Computational Intelligence for Big Data Analysis
ISBN: 3319362003 ISBN-13(EAN): 9783319362007
Издательство: Springer
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Цена: 95770.00 T
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Описание: The work presented in this book is a combination of theoretical advancements of big data analysis, cloud computing, and their potential applications in scientific computing. The book discusses major issues pertaining to big data analysis using computational intelligence techniques and some issues of cloud computing.

Автор: Mohammad Moshirpour; Behrouz Far; Reda Alhajj
Название: Highlighting the Importance of Big Data Management and Analysis for Various Applications
ISBN: 3319602543 ISBN-13(EAN): 9783319602547
Издательство: Springer
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Цена: 83850.00 T
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Описание: This book addresses the impacts of various types of services such as infrastructure, platforms, software, and business processes that cloud computing and Big Data have introduced into business.

Автор: Oleg Granichin; Zeev (Vladimir) Volkovich; Dvora T
Название: Randomized Algorithms in Automatic Control and Data Mining
ISBN: 3662522918 ISBN-13(EAN): 9783662522912
Издательство: Springer
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Цена: 95770.00 T
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Описание: In the fields of data mining and control, the huge amount of unstructured data and the presence of uncertainty in system descriptions have always been critical issues.

Автор: Gisele L. Pappa; Alex Freitas
Название: Automating the Design of Data Mining Algorithms
ISBN: 3642261256 ISBN-13(EAN): 9783642261251
Издательство: Springer
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Цена: 130430.00 T
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Описание: This unique text seeks to automate the design of a data mining algorithm. It first overviews data mining and evolutionary algorithms then discusses the design of a new genetic programming system for automating the design of full rule induction algorithms.

Автор: Zbigniew Michalewicz
Название: Genetic Algorithms + Data Structures = Evolution Programs
ISBN: 3540606769 ISBN-13(EAN): 9783540606765
Издательство: Springer
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Цена: 102480.00 T
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Описание: Hence evolution programming techniques, based on genetic algorithms, are applicable to many hard optimization problems, such as optimization of functions with linear and nonlinear constraints, the traveling salesman problem, and problems of scheduling, partitioning, and control.

Автор: Oleg Granichin; Zeev (Vladimir) Volkovich; Dvora T
Название: Randomized Algorithms in Automatic Control and Data Mining
ISBN: 3642547850 ISBN-13(EAN): 9783642547850
Издательство: Springer
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Цена: 130610.00 T
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Описание: In the fields of data mining and control, the huge amount of unstructured data and the presence of uncertainty in system descriptions have always been critical issues.