Time Series Indexing

Author : Mihalis Tsoukalos
Publisher : Packt Publishing Ltd
Page : 249 pages
File Size : 42,6 Mb
Release : 2023-06-30
Category : Technology & Engineering
ISBN : 9781838822873

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Time Series Indexing by Mihalis Tsoukalos Pdf

Build and use the most popular time series index available today with Python to search and join time series at the subsequence level Purchase of the print or Kindle book includes a free PDF eBook Key Features Learn how to implement algorithms and techniques from research papers Get to grips with building time series indexes using iSAX Leverage iSAX to solve real-world time series problems Book Description Time series are everywhere, ranging from financial data and system metrics to weather stations and medical records. Being able to access, search, and compare time series data quickly is essential, and this comprehensive guide enables you to do just that by helping you explore SAX representation and the most effective time series index, iSAX. The book begins by teaching you about the implementation of SAX representation in Python as well as the iSAX index, along with the required theory sourced from academic research papers. The chapters are filled with figures and plots to help you follow the presented topics and understand key concepts easily. But what makes this book really great is that it contains the right amount of knowledge about time series indexing using the right amount of theory and practice so that you can work with time series and develop time series indexes successfully. Additionally, the presented code can be easily ported to any other modern programming language, such as Swift, Java, C, C++, Ruby, Kotlin, Go, Rust, and JavaScript. By the end of this book, you'll have learned how to harness the power of iSAX and SAX representation to efficiently index and analyze time series data and will be equipped to develop your own time series indexes and effectively work with time series data. What you will learn Find out how to develop your own Python packages and write simple Python tests Understand what a time series index is and why it is useful Gain a theoretical and practical understanding of operating and creating time series indexes Discover how to use SAX representation and the iSAX index Find out how to search and compare time series Utilize iSAX visualizations to aid in the interpretation of complex or large time series Who this book is for This book is for practitioners, university students working with time series, researchers, and anyone looking to learn more about time series. Basic knowledge of UNIX, Linux, and Python and an understanding of basic programming concepts are needed to grasp the topics in this book. This book will also be handy for people who want to learn how to read research papers, learn from them, and implement their algorithms.

Author : Jake VanderPlas
Publisher : "O'Reilly Media, Inc."
Page : 743 pages
File Size : 46,5 Mb
Release : 2016-11-21
Category : Computers
ISBN : 9781491912133

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Python Data Science Handbook by Jake VanderPlas Pdf

For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms

Author : Jyotiprasad Medhi
Publisher : New Age International
Page : 456 pages
File Size : 54,8 Mb
Release : 1992
Category : Mathematics
ISBN : 8122404197

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Statistical Methods by Jyotiprasad Medhi Pdf

The Preface Elucidates That The Text Is Designed For Degree Courses In India. However, I Imagine That It Could Play A Useful Role For Those In Britain. It Is Mainly Intended As An Introductory Text For Those Studying Social Sciences And Economics. Individuals From Other Disciplines Would, No Doubt, Still Find It Useful As A General Reference.The Chapters Are Well Written And Easy To Follow. An Appealing Feature Of The Book Is That Much Emphasis Is Placed On The Understanding And Application Of Statistical Methods. There Is Avoidance Of Excessive Presentation Of Formulae. For These Reasons Alone I Think That Students Will Find The Text Attractive. Each Chapter Finishes With A Series Of Well-Formulated Questions, Which Test The Readers' Understanding.The Two Chapters On Statistical Inference And Tests Of Significance Are Excellent.It Is A Comprehensive And Interesting Text, One That I Think Most Students Would Find Useful. Indeed, It Is An Useful Addition To My Library, Having Already Referred To It Often. The Statistician, London, Vol. 45, No. 3 (1996).

Author : Alejandro Ramírez-Rojas,Leonardo Di G. Sigalotti,Elsa Leticia Flores Márquez,Otto Rendón
Publisher : Elsevier
Page : 406 pages
File Size : 45,6 Mb
Release : 2019-08-02
Category : Science
ISBN : 9780128149027

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Time Series Analysis in Seismology by Alejandro Ramírez-Rojas,Leonardo Di G. Sigalotti,Elsa Leticia Flores Márquez,Otto Rendón Pdf

Time Series Analysis in Seismology: Practical Applications provides technical assistance and coverage of available methods to professionals working in the field of seismology. Beginning with a thorough review of open problems in geophysics, including tectonic plate dynamics, localization of solitons, and forecasting, the book goes on to describe the various types of time series or punctual processes obtained from those systems. Additionally, the book describes a variety of methods and techniques relating to seismology and includes a discussion of future developments and improvements. Time Series Analysis in Seismology offers a concise presentation of the most recent advances in the analysis of geophysical data, particularly with regard to seismology, making it a valuable tool for researchers and students working in seismology and geophysics. Presents the necessary tools for time series analysis as it relates to seismology in a compact and consistent manner Includes a discussion of technical resources that can be applied to time series data analysis across multiple disciplines Describes the methods and techniques available for solving problems related to the analysis of complex data sets Provides exercises at the end of each chapter to enhance comprehension

Author : Julio Ponce,Adem Karahoca
Publisher : BoD – Books on Demand
Page : 404 pages
File Size : 53,7 Mb
Release : 2009-01-01
Category : Computers
ISBN : 9783902613530

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Data Mining and Knowledge Discovery in Real Life Applications by Julio Ponce,Adem Karahoca Pdf

This book presents four different ways of theoretical and practical advances and applications of data mining in different promising areas like Industrialist, Biological, and Social. Twenty six chapters cover different special topics with proposed novel ideas. Each chapter gives an overview of the subjects and some of the chapters have cases with offered data mining solutions. We hope that this book will be a useful aid in showing a right way for the students, researchers and practitioners in their studies.

Author : Mihalis Tsoukalos
Publisher : Unknown
Page : 0 pages
File Size : 54,8 Mb
Release : 2023-06-30
Category : Electronic
ISBN : 1838821953

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Time Series Indexing by Mihalis Tsoukalos Pdf

Build and use the most popular time series index available today with Python to search and join time series at the subsequence level Purchase of the print or Kindle book includes a free PDF eBook Key Features: Learn how to implement algorithms and techniques from research papers Get to grips with building time series indexes using iSAX Leverage iSAX to solve real-world time series problems Book Description: Time series are everywhere, ranging from financial data and system metrics to weather stations and medical records. Being able to access, search, and compare time series data quickly is essential, and this comprehensive guide enables you to do just that by helping you explore SAX representation and the most effective time series index, iSAX. The book begins by teaching you about the implementation of SAX representation in Python as well as the iSAX index, along with the required theory sourced from academic research papers. The chapters are filled with figures and plots to help you follow the presented topics and understand key concepts easily. But what makes this book really great is that it contains the right amount of knowledge about time series indexing using the right amount of theory and practice so that you can work with time series and develop time series indexes successfully. Additionally, the presented code can be easily ported to any other modern programming language, such as Swift, Java, C, C++, Ruby, Kotlin, Go, Rust, and JavaScript. By the end of this book, you'll have learned how to harness the power of iSAX and SAX representation to efficiently index and analyze time series data and will be equipped to develop your own time series indexes and effectively work with time series data. What You Will Learn: Find out how to develop your own Python packages and write simple Python tests Understand what a time series index is and why it is useful Gain a theoretical and practical understanding of operating and creating time series indexes Discover how to use SAX representation and the iSAX index Find out how to search and compare time series Utilize iSAX visualizations to aid in the interpretation of complex or large time series Who this book is for: This book is for practitioners, university students working with time series, researchers, and anyone looking to learn more about time series. Basic knowledge of UNIX, Linux, and Python and an understanding of basic programming concepts are needed to grasp the topics in this book. This book will also be handy for people who want to learn how to read research papers, learn from them, and implement their algorithms.

Author : Abdelkader Hameurlain,A Min Tjoa
Publisher : Springer Nature
Page : 175 pages
File Size : 51,8 Mb
Release : 2023-02-08
Category : Computers
ISBN : 9783662668634

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Transactions on Large-Scale Data- and Knowledge-Centered Systems LIII by Abdelkader Hameurlain,A Min Tjoa Pdf

The LNCS journal Transactions on Large-scale Data and Knowledge-centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing (e.g. computing resources, services, metadata, data sources) across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. This, the 53rd issue of Transactions on Large-scale Data and Knowledge-centered Systems, contains six fully revised selected regular papers. Topics covered include time series management from edge to cloud, segmentation for time series representation, similarity research, semantic similarity in a taxonomy, linked data semantic distance, linguistics-informed natural language processing, graph neural network, protected features, imbalanced data, causal consistency in distributed databases, actor model, and elastic horizontal scalability.

Author : Michael J. North,Charles M. Macal
Publisher : Oxford University Press
Page : 328 pages
File Size : 40,5 Mb
Release : 2007-03-01
Category : Business & Economics
ISBN : 0198038410

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Managing Business Complexity by Michael J. North,Charles M. Macal Pdf

Agent-based modeling and simulation (ABMS), a way to simulate a large number of choices by individual actors, is one of the most exciting practical developments in business modeling since the invention of relational databases. It represents a new way to understand data and generate information that has never been available before--a way for businesses to view the future and to understand and anticipate the likely effects of their decisions on their markets and industries. It thus promises to have far-reaching effects on the way that businesses in many areas use computers to support practical decision-making. Managing Business Complexity is the first complete business-oriented agent-based modeling and simulation resource. It has three purposes: first, to teach readers how to think about ABMS, that is, about agents and their interactions; second, to teach readers how to explain the features and advantages of ABMS to other people and third, to teach readers how to actually implement ABMS by building agent-based simulations. It is intended to be a complete ABMS resource, accessible to readers who haven't had any previous experience in building agent-based simulations, or any other kinds of models, for that matter. It is also a collection of ABMS business applications resources, all assembled in one place for the first time. In short, Managing Business Complexity addresses who needs ABMS and why, where and when ABMS can be applied to the everyday business problems that surround us, and how specifically to build these powerful agent-based models.

Author : Steven B. Cowan,James S. Spiegel
Publisher : Bloomsbury Publishing USA
Page : 223 pages
File Size : 43,9 Mb
Release : 2016-02-25
Category : Philosophy
ISBN : 9781628924077

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Idealism and Christian Philosophy by Steven B. Cowan,James S. Spiegel Pdf

When it comes to contemporary philosophical problems, metaphysical idealism-or Berkeleyan immaterialism-is not taken seriously by most philosophers, not to mention the typical Christian layperson. This state of affairs deserves some attempt at rectification, since Idealism has considerable explanatory power as a metaphysical thesis and provides numerous practical and theoretical benefits. Such thinkers as George Berkeley and Jonathan Edwards believed that Idealism is especially amenable to a Christian perspective, both because it provides a plausible way of conceptualizing the world from a theistic standpoint and because it effectively addresses skeptical challenges to the Christian faith. The contributors to this volume explore a variety of ways in which the case can be made for this claim, including potential solutions to philosophical problems related to the nature of time, the ontology of physical objects, the mind-body problem, and the nature of science.

Author : Tahera Firdose
Publisher : Orange Education Pvt Ltd
Page : 384 pages
File Size : 43,9 Mb
Release : 2024-06-10
Category : Computers
ISBN : 9788197256240

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Ultimate Pandas for Data Manipulation and Visualization by Tahera Firdose Pdf

TAGLINE Unlock the power of Data Manipulation with Pandas. KEY FEATURES ● Master Pandas from basics to advanced and its data manipulation techniques. ● Visualize data effectively with Matplotlib and explore data efficiently. ● Learn through hands-on examples and practical real-world use cases. DESCRIPTION Unlock the power of Pandas, the essential Python library for data analysis and manipulation. This comprehensive guide takes you from the basics to advanced techniques, ensuring you master every aspect of pandas. You'll start with an introduction to pandas and data analysis, followed by in-depth explorations of pandas Series and DataFrame, the core data structures. Learn essential skills for data cleaning and filtering, and master grouping and aggregation techniques to summarize and analyze your data sets effectively. Discover how to reshape and pivot data, join and merge multiple datasets, and handle time series analysis. Enhance your data analysis with compelling visualizations using Matplotlib, and apply your knowledge in a real-world scenario by analyzing bank customer churn. Through hands-on examples and practical use cases, this book equips you with the tools to clean, filter, aggregate, reshape, merge, and visualize data effectively, transforming it into actionable insights. WHAT WILL YOU LEARN ● Wrangle data efficiently using Pandas' cleaning, filtering, and transformation techniques. ● Unlock hidden patterns with advanced grouping, joining, and merging operations. ● Master time series analysis with Pandas to extract valuable insights from your data. ● Apply Pandas to real-world scenarios like customer churn analysis and financial modeling. ● Unleash the power of data visualization with Matplotlib and craft compelling charts and graphs. ● Enhance your workflow with essential Pandas optimizations and performance tips. WHO IS THIS BOOK FOR? This book is ideal for aspiring data scientists, analysts, and Python enthusiasts looking to enhance their data manipulation skills using Pandas. Familiarity with Python programming basics and a basic understanding of data structures will greatly benefit readers as they delve into the concepts presented in this book. TABLE OF CONTENTS 1. Introduction to Pandas and Data Analysis 2. Pandas Series 3. Pandas DataFrame 4. Data Cleaning with Pandas 5. Data Filtering with Pandas 6. Grouping and Aggregating Data 7. Reshaping and Pivoting in Pandas 8. Joining and Merging Data in Pandas 9. Introduction to Time Series Analysis in Pandas 10. Visualization Using Matplotlib 11. Analyzing Bank Customer Churn Using Pandas Index

Author : Mark Last,Abraham Kandel,Horst Bunke
Publisher : World Scientific
Page : 205 pages
File Size : 52,9 Mb
Release : 2004
Category : Mathematics
ISBN : 9789812382900

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Data Mining in Time Series Databases by Mark Last,Abraham Kandel,Horst Bunke Pdf

Adding the time dimension to real-world databases produces Time Series Databases (TSDB) and introduces new aspects and difficulties to data mining and knowledge discovery. This book covers the state-of-the-art methodology for mining time series databases. The novel data mining methods presented in the book include techniques for efficient segmentation, indexing, and classification of noisy and dynamic time series. A graph-based method for anomaly detection in time series is described and the book also studies the implications of a novel and potentially useful representation of time series as strings. The problem of detecting changes in data mining models that are induced from temporal databases is additionally discussed. Contents: A Survey of Recent Methods for Efficient Retrieval of Similar Time Sequences (H M Lie); Indexing of Compressed Time Series (E Fink & K Pratt); Boosting Interval-Based Literal: Variable Length and Early Classification (J J Rodriguez Diez); Segmenting Time Series: A Survey and Novel Approach (E Keogh et al.); Indexing Similar Time Series under Conditions of Noise (M Vlachos et al.); Classification of Events in Time Series of Graphs (H Bunke & M Kraetzl); Median Strings--A Review (X Jiang et al.); Change Detection in Classfication Models of Data Mining (G Zeira et al.). Readership: Graduate students, reseachers and practitioners in the fields of data mining, machine learning, databases and statistics.

Author : Dr. (Prof.) Nirdosh Agarwa,Dr. Ashish Kaushal
Publisher : Thakur Publication Private Limited
Page : 312 pages
File Size : 46,8 Mb
Release : 2021-01-05
Category : Education
ISBN : 9789354800757

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Business Statistics (English Edition) by Dr. (Prof.) Nirdosh Agarwa,Dr. Ashish Kaushal Pdf

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Author : Robert Johansson
Publisher : Apress
Page : 505 pages
File Size : 48,5 Mb
Release : 2015-10-07
Category : Computers
ISBN : 9781484205532

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Numerical Python by Robert Johansson Pdf

Numerical Python by Robert Johansson shows you how to leverage the numerical and mathematical modules in Python and its Standard Library as well as popular open source numerical Python packages like NumPy, FiPy, matplotlib and more to numerically compute solutions and mathematically model applications in a number of areas like big data, cloud computing, financial engineering, business management and more. After reading and using this book, you'll get some takeaway case study examples of applications that can be found in areas like business management, big data/cloud computing, financial engineering (i.e., options trading investment alternatives), and even games. Up until very recently, Python was mostly regarded as just a web scripting language. Well, computational scientists and engineers have recently discovered the flexibility and power of Python to do more. Big data analytics and cloud computing programmers are seeing Python's immense use. Financial engineers are also now employing Python in their work. Python seems to be evolving as a language that can even rival C++, Fortran, and Pascal/Delphi for numerical and mathematical computations.

Author : Marguerite C. Burk
Publisher : Unknown
Page : 124 pages
File Size : 43,7 Mb
Release : 1961
Category : Food consumption
ISBN : UIUC:30112019252110

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Measures and Procedures for Analysis of U.S. Food Consumption by Marguerite C. Burk Pdf

Author : Shuigeng Zhou,Songmao Zhang,George Karypis
Publisher : Springer Science & Business Media
Page : 812 pages
File Size : 55,6 Mb
Release : 2012-12-09
Category : Computers
ISBN : 9783642355271

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Advanced Data Mining and Applications by Shuigeng Zhou,Songmao Zhang,George Karypis Pdf

This book constitutes the refereed proceedings of the 8th International Conference on Advanced Data Mining and Applications, ADMA 2012, held in Nanjing, China, in December 2012. The 32 regular papers and 32 short papers presented in this volume were carefully reviewed and selected from 168 submissions. They are organized in topical sections named: social media mining; clustering; machine learning: algorithms and applications; classification; prediction, regression and recognition; optimization and approximation; mining time series and streaming data; Web mining and semantic analysis; data mining applications; search and retrieval; information recommendation and hiding; outlier detection; topic modeling; and data cube computing.