Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.
Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.
Please visit the book companion website at https: //www.cs.waikato.ac.nz/ ml/weka/book.html.
It contains
Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book
Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book
Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.
Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects
Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods
Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface
Includes open-access online courses that introduce practical applications of the material in the book
Автор: Alexander Mehler; Kai-Uwe K?hnberger; Henning Lobi Название: Modeling, Learning, and Processing of Text-Technological Data Structures ISBN: 3642269443 ISBN-13(EAN): 9783642269448 Издательство: Springer Рейтинг: Цена: 23508.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Researchers in many disciplines have been concerned with modeling textual data in order to account for texts as the primary information unit of written communication.
Автор: Navarro Название: Compact Data Structures ISBN: 1107152380 ISBN-13(EAN): 9781107152380 Издательство: Cambridge Academ Рейтинг: Цена: 11880.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Compact data structures are essential tools for efficiently handling massive amounts of data by exploiting the memory hierarchy and for reducing the resources needed for distributed and mobile applications. This first comprehensive book on the topic focuses on the structures that are most relevant for practical use.
Автор: Kai v. Luck; Heinz Marburger Название: Management and Processing of Complex Data Structures ISBN: 3540578021 ISBN-13(EAN): 9783540578024 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume of conference proceedings focuses on the management and processing of complex data structures. Most of the contributors stress the need for new or extended formalisms and their deductive capabilities, analyzing the properties needed to manage complex structures.
Автор: Agarwal, Dr Basant, Baka, Benjamin Название: Hands-On Data Structures and Algorithms with Python 2 ed ISBN: 1788995570 ISBN-13(EAN): 9781788995573 Издательство: Неизвестно Рейтинг: Цена: 8091.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Data structures help us to organize and align the data in a very efficient way. This book will surely help you to learn important and essential data structures through Python implementation for better understanding of the concepts.
Описание: This monograph deals with mathematical constructions that are foundational in such an important area of data mining as pattern recognition. By using combinatorial and graph theoretic techniques, a closer look is taken at infeasible systems of linear inequalities, whose generalized solutions act as building blocks of geometric decision rules for pattern recognition.Infeasible systems of linear inequalities prove to be a key object in pattern recognition problems described in geometric terms thanks to the committee method. Such infeasible systems of inequalities represent an important special subclass of infeasible systems of constraints with a monotonicity property - systems whose multi-indices of feasible subsystems form abstract simplicial complexes (independence systems), which are fundamental objects of combinatorial topology.The methods of data mining and machine learning discussed in this monograph form the foundation of technologies like big data and deep learning, which play a growing role in many areas of human-technology interaction and help to find solutions, better solutions and excellent solutions. Contents: PrefacePattern recognition, infeasible systems of linear inequalities, and graphsInfeasible monotone systems of constraintsComplexes, (hyper)graphs, and inequality systemsPolytopes, positive bases, and inequality systemsMonotone Boolean functions, complexes, graphs, and inequality systemsInequality systems, committees, (hyper)graphs, and alternative coversBibliographyList of notationIndex
Автор: Andrade Название: Fundamentals of Stream Processing ISBN: 1107015545 ISBN-13(EAN): 9781107015548 Издательство: Cambridge Academ Рейтинг: Цена: 13781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book teaches fundamentals of the stream processing paradigm that addresses performance, scalability and usability challenges in extracting insights from massive amounts of live, streaming data. It presents core principles behind application design, system infrastructure and analytics, coupled with real-world examples for a comprehensive understanding of the stream processing area.
Автор: C.Lee Giles; Marco Gori Название: Adaptive Processing of Sequences and Data Structures ISBN: 3540643419 ISBN-13(EAN): 9783540643418 Издательство: Springer Рейтинг: Цена: 8099.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This text is devoted to adaptive processing of structured information similar to flexible and intelligent information processing by humans. It allows for a mixture of sequential and parallel processing of symbolic as well as sub-symbolic information with deterministic and probabilistic frameworks.
Автор: Matveev, Andrey O., Название: Pattern recognition on oriented matroids / ISBN: 3110530716 ISBN-13(EAN): 9783110530711 Издательство: Walter de Gruyter Рейтинг: Цена: 18586.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Pattern Recognition on Oriented Matroids covers a range of innovative problems in combinatorics, poset and graph theories, optimization, and number theory that constitute a far-reaching extension of the arsenal of committee methods in pattern recognition. The groundwork for the modern committee theory was laid in the mid-1960s, when it was shown that the familiar notion of solution to a feasible system of linear inequalities has ingenious analogues which can serve as collective solutions to infeasible systems. A hierarchy of dialects in the language of mathematics, for instance, open cones in the context of linear inequality systems, regions of hyperplane arrangements, and maximal covectors (or topes) of oriented matroids, provides an excellent opportunity to take a fresh look at the infeasible system of homogeneous strict linear inequalities - the standard working model for the contradictory two-class pattern recognition problem in its geometric setting. The universal language of oriented matroid theory considerably simplifies a structural and enumerative analysis of applied aspects of the infeasibility phenomenon.
The present book is devoted to several selected topics in the emerging theory of pattern recognition on oriented matroids: the questions of existence and applicability of matroidal generalizations of committee decision rules and related graph-theoretic constructions to oriented matroids with very weak restrictions on their structural properties; a study (in which, in particular, interesting subsequences of the Farey sequence appear naturally) of the hierarchy of the corresponding tope committees; a description of the three-tope committees that are the most attractive approximation to the notion of solution to an infeasible system of linear constraints; an application of convexity in oriented matroids as well as blocker constructions in combinatorial optimization and in poset theory to enumerative problems on tope committees; an attempt to clarify how elementary changes (one-element reorientations) in an oriented matroid affect the family of its tope committees; a discrete Fourier analysis of the important family of critical tope committees through rank and distance relations in the tope poset and the tope graph; the characterization of a key combinatorial role played by the symmetric cycles in hypercube graphs.
Contents Oriented Matroids, the Pattern Recognition Problem, and Tope Committees Boolean Intervals Dehn-Sommerville Type Relations Farey Subsequences Blocking Sets of Set Families, and Absolute Blocking Constructions in Posets Committees of Set Families, and Relative Blocking Constructions in Posets Layers of Tope Committees Three-Tope Committees Halfspaces, Convex Sets, and Tope Committees Tope Committees and Reorientations of Oriented Matroids Topes and Critical Committees Critical Committees and Distance Signals Symmetric Cycles in the Hypercube Graphs
Автор: Zhang Tsinghua University Press Liyi Название: Blind Equalization in Neural Networks ISBN: 3110449625 ISBN-13(EAN): 9783110449624 Издательство: Walter de Gruyter Цена: 18586.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book begins with an introduction of blind equalization theory and its application in neural networks, then discusses the algorithms in recurrent networks, fuzzy networks and other frequently-studied neural networks. Each algorithm is accompanied by derivation, modeling and simulation, making the book an essential reference for electrical engineers, computer intelligence researchers and neural scientists.
Автор: Hassanieh Haitham Название: The Sparse Fourier Transform ISBN: 1947487043 ISBN-13(EAN): 9781947487048 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 10352.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The Fourier transform is one of the most fundamental tools for computing the frequency representation of signals. It plays a central role in signal processing, communications, audio and video compression, medical imaging, genomics, astronomy, as well as many other areas. Because of its widespread use, fast algorithms for computing the Fourier transform can benefit a large number of applications. The fastest algorithm for computing the Fourier transform is the Fast Fourier Transform (FFT), which runs in near-linear time making it an indispensable tool for many applications. However, today, the runtime of the FFT algorithm is no longer fast enough especially for big data problems where each dataset can be few terabytes. Hence, faster algorithms that run in sublinear time, i.e., do not even sample all the data points, have become necessary.This book addresses the above problem by developing the Sparse Fourier Transform algorithms and building practical systems that use these algorithms to solve key problems in six different applications: wireless networks; mobile systems; computer graphics; medical imaging; biochemistry; and digital circuits.This is a revised version of the thesis that won the 2016 ACM Doctoral Dissertation Award.
Автор: Haitham Hassanieh Название: The Sparse Fourier Transform ISBN: 1947487078 ISBN-13(EAN): 9781947487079 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 12860.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The Fourier transform is one of the most fundamental tools for computing the frequency representation of signals. It plays a central role in signal processing, communications, audio and video compression, medical imaging, genomics, astronomy, as well as many other areas. Because of its widespread use, fast algorithms for computing the Fourier transform can benefit a large number of applications. The fastest algorithm for computing the Fourier transform is the Fast Fourier Transform (FFT), which runs in near-linear time making it an indispensable tool for many applications. However, today, the runtime of the FFT algorithm is no longer fast enough especially for big data problems where each dataset can be few terabytes. Hence, faster algorithms that run in sublinear time, i.e., do not even sample all the data points, have become necessary.This book addresses the above problem by developing the Sparse Fourier Transform algorithms and building practical systems that use these algorithms to solve key problems in six different applications: wireless networks; mobile systems; computer graphics; medical imaging; biochemistry; and digital circuits.This is a revised version of the thesis that won the 2016 ACM Doctoral Dissertation Award.
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