Foundations Of Multidimensional And Metric Data Structures
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Foundations Of Multidimensional And Metric Data Structures
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Author : Hanan Samet
language : en
Publisher: Morgan Kaufmann
Release Date : 2006-08-08
Foundations Of Multidimensional And Metric Data Structures written by Hanan Samet and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-08-08 with Computers categories.
Publisher Description
Foundations Of Multidimensional And Metric Data Structures
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Author :
language : en
Publisher:
Release Date : 2012
Foundations Of Multidimensional And Metric Data Structures written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.
Foundations Of Data Science
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Author : Avrim Blum
language : en
Publisher: Cambridge University Press
Release Date : 2020-01-23
Foundations Of Data Science written by Avrim Blum and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-23 with Computers categories.
Covers mathematical and algorithmic foundations of data science: machine learning, high-dimensional geometry, and analysis of large networks.
Applications Of Spatial Data Structures
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Author : Hanan Samet
language : en
Publisher: Addison Wesley Publishing Company
Release Date : 1990
Applications Of Spatial Data Structures written by Hanan Samet and has been published by Addison Wesley Publishing Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Computers categories.
Similarity Search
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Author : Pavel Zezula
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-06-07
Similarity Search written by Pavel Zezula and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-06-07 with Computers categories.
The area of similarity searching is a very hot topic for both research and c- mercial applications. Current data processing applications use data with c- siderably less structure and much less precise queries than traditional database systems. Examples are multimedia data like images or videos that offer query by example search, product catalogs that provide users with preference based search, scientific data records from observations or experimental analyses such as biochemical and medical data, or XML documents that come from hetero- neous data sources on the Web or in intranets and thus does not exhibit a global schema. Such data can neither be ordered in a canonical manner nor meani- fully searched by precise database queries that would return exact matches. This novel situation is what has given rise to similarity searching, also - ferred to as content based or similarity retrieval. The most general approach to similarity search, still allowing construction of index structures, is modeled in metric space. In this book. Prof. Zezula and his co authors provide the first monograph on this topic, describing its theoretical background as well as the practical search tools of this innovative technology.
Multidimensional Scaling
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Author : Joseph B. Kruskal
language : en
Publisher: SAGE Publications
Release Date : 1978-01-01
Multidimensional Scaling written by Joseph B. Kruskal and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 1978-01-01 with Social Science categories.
Outlines a set of techniques that enable a researcher to discuss the "hidden structure" of large data bases. These techniques use proximities, measures which indicate how similar or different objects are, to find a configuration of points which reflects the structure in the data.
Data Structures And Algorithm Analysis In C
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Author : Mark Allen Weiss
language : en
Publisher:
Release Date : 2003
Data Structures And Algorithm Analysis In C written by Mark Allen Weiss and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with C++ (Computer program language) categories.
In this second edition of his successful book, experienced teacher and author Mark Allen Weiss continues to refine and enhance his innovative approach to algorithms and data structures. Written for the advanced data structures course, this text highlights theoretical topics such as abstract data types and the efficiency of algorithms, as well as performance and running time. Before covering algorithms and data structures, the author provides a brief introduction to C++ for programmers unfamiliar with the language. Dr Weiss's clear writing style, logical organization of topics, and extensive use of figures and examples to demonstrate the successive stages of an algorithm make this an accessible, valuable text. New to this Edition *An appendix on the Standard Template Library (STL) *C++ code, tested on multiple platforms, that conforms to the ANSI ISO final draft standard 0201361221B04062001
A Practical Introduction To Data Structures And Algorithm Analysis
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Author : Clifford A. Shaffer
language : en
Publisher:
Release Date : 2001
A Practical Introduction To Data Structures And Algorithm Analysis written by Clifford A. Shaffer and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Computers categories.
This practical text contains fairly "traditional" coverage of data structures with a clear and complete use of algorithm analysis, and some emphasis on file processing techniques as relevant to modern programmers. It fully integrates OO programming with these topics, as part of the detailed presentation of OO programming itself.Chapter topics include lists, stacks, and queues; binary and general trees; graphs; file processing and external sorting; searching; indexing; and limits to computation.For programmers who need a good reference on data structures.
Analysis Of Multidimensional Poverty
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Author : Louis-Marie Asselin
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-08-29
Analysis Of Multidimensional Poverty written by Louis-Marie Asselin and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-08-29 with Business & Economics categories.
Poverty is a paradoxical state. Recognizable in the eld for any sensitive observer who travels in remote rural areas and urban slums and meets marginalized people in a given society, poverty still remains a challenge to conceptual formalization and to measurement that is consistent with such formalization. The analysis of poverty is multidisciplinary. It goes from ethics to economics, from political science to human biology, and any type of measurement rests on mathematics. Moreover, poverty is multifaceted according to the types of deprivation, and it is also gender and age speci c. A vector of variables is required, which raises a substantial problem for individual and group comparisons necessary to equity analysis. Multidimension- ity also complicates the aggregation necessary to perform the ef ciency analysis of policies. In the case of income poverty, these two problems, equity and ef ciency, have bene ted from very signi cant progress in the eld of economics. Similar achievements are still to come in the area of multidimensional poverty. Within this general background, this book has a very modest and narrow-scoped objective. It proposes an operational methodology for measuring multidimensional poverty, independent from the conceptual origin, the size and the qualitative as well as the quantitative nature of the primary indicators used to describe the poverty of an individual, a household or a sociodemographic entity.
The Data Science Design Manual
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Author : Steven S. Skiena
language : en
Publisher: Springer
Release Date : 2017-07-01
The Data Science Design Manual written by Steven S. Skiena and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-01 with Computers categories.
This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: Contains “War Stories,” offering perspectives on how data science applies in the real world Includes “Homework Problems,” providing a wide range of exercises and projects for self-study Provides a complete set of lecture slides and online video lectures at www.data-manual.com Provides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapter Recommends exciting “Kaggle Challenges” from the online platform Kaggle Highlights “False Starts,” revealing the subtle reasons why certain approaches fail Offers examples taken from the data science television show “The Quant Shop” (www.quant-shop.com)
