Pattern Recognition And Classification In Time Series Data

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Pattern Recognition and Classification in Time Series Data

Volna, Eva,Kotyrba, Martin,Janosek, Michal
Pattern Recognition and Classification in Time Series Data Book PDF

Author : Volna, Eva,Kotyrba, Martin,Janosek, Michal
Publisher : IGI Global
Page : 282 pages
File Size : 53,7 Mb
Release : 2016-07-22
Category : Computers
ISBN : 9781522505662

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Pattern Recognition and Classification in Time Series Data by Volna, Eva,Kotyrba, Martin,Janosek, Michal Pdf

Patterns can be any number of items that occur repeatedly, whether in the behaviour of animals, humans, traffic, or even in the appearance of a design. As technologies continue to advance, recognizing, mimicking, and responding to all types of patterns becomes more precise. Pattern Recognition and Classification in Time Series Data focuses on intelligent methods and techniques for recognizing and storing dynamic patterns. Emphasizing topics related to artificial intelligence, pattern management, and algorithm development, in addition to practical examples and applications, this publication is an essential reference source for graduate students, researchers, and professionals in a variety of computer-related disciplines.

Time Series Clustering and Classification

Elizabeth Ann Maharaj,Pierpaolo D'Urso,Jorge Caiado
Time Series Clustering and Classification Book PDF

Author : Elizabeth Ann Maharaj,Pierpaolo D'Urso,Jorge Caiado
Publisher : CRC Press
Page : 228 pages
File Size : 45,5 Mb
Release : 2019-03-19
Category : Mathematics
ISBN : 9780429608827

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Time Series Clustering and Classification by Elizabeth Ann Maharaj,Pierpaolo D'Urso,Jorge Caiado Pdf

The beginning of the age of artificial intelligence and machine learning has created new challenges and opportunities for data analysts, statisticians, mathematicians, econometricians, computer scientists and many others. At the root of these techniques are algorithms and methods for clustering and classifying different types of large datasets, including time series data. Time Series Clustering and Classification includes relevant developments on observation-based, feature-based and model-based traditional and fuzzy clustering methods, feature-based and model-based classification methods, and machine learning methods. It presents a broad and self-contained overview of techniques for both researchers and students. Features Provides an overview of the methods and applications of pattern recognition of time series Covers a wide range of techniques, including unsupervised and supervised approaches Includes a range of real examples from medicine, finance, environmental science, and more R and MATLAB code, and relevant data sets are available on a supplementary website

Machine Learning for Time-Series with Python

Ben Auffarth
Machine Learning for Time Series with Python Book PDF

Author : Ben Auffarth
Publisher : Packt Publishing Ltd
Page : 371 pages
File Size : 54,6 Mb
Release : 2021-10-29
Category : Computers
ISBN : 9781801816106

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Machine Learning for Time-Series with Python by Ben Auffarth Pdf

Get better insights from time-series data and become proficient in model performance analysis Key FeaturesExplore popular and modern machine learning methods including the latest online and deep learning algorithmsLearn to increase the accuracy of your predictions by matching the right model with the right problemMaster time series via real-world case studies on operations management, digital marketing, finance, and healthcareBook Description The Python time-series ecosystem is huge and often quite hard to get a good grasp on, especially for time-series since there are so many new libraries and new models. This book aims to deepen your understanding of time series by providing a comprehensive overview of popular Python time-series packages and help you build better predictive systems. Machine Learning for Time-Series with Python starts by re-introducing the basics of time series and then builds your understanding of traditional autoregressive models as well as modern non-parametric models. By observing practical examples and the theory behind them, you will become confident with loading time-series datasets from any source, deep learning models like recurrent neural networks and causal convolutional network models, and gradient boosting with feature engineering. This book will also guide you in matching the right model to the right problem by explaining the theory behind several useful models. You'll also have a look at real-world case studies covering weather, traffic, biking, and stock market data. By the end of this book, you should feel at home with effectively analyzing and applying machine learning methods to time-series. What you will learnUnderstand the main classes of time series and learn how to detect outliers and patternsChoose the right method to solve time-series problemsCharacterize seasonal and correlation patterns through autocorrelation and statistical techniquesGet to grips with time-series data visualizationUnderstand classical time-series models like ARMA and ARIMAImplement deep learning models, like Gaussian processes, transformers, and state-of-the-art machine learning modelsBecome familiar with many libraries like Prophet, XGboost, and TensorFlowWho this book is for This book is ideal for data analysts, data scientists, and Python developers who want instantly useful and practical recipes to implement today, and a comprehensive reference book for tomorrow. Basic knowledge of the Python Programming language is a must, while familiarity with statistics will help you get the most out of this book.

Data Mining in Time Series Databases

Mark Last,Abraham Kandel,Horst Bunke
Data Mining in Time Series Databases Book PDF

Author : Mark Last,Abraham Kandel,Horst Bunke
Publisher : World Scientific
Page : 205 pages
File Size : 53,7 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.

Fuzzy Engineering Toward Human Friendly Systems

Toshiro Terano
Fuzzy Engineering Toward Human Friendly Systems Book PDF

Author : Toshiro Terano
Publisher : IOS Press
Page : 1174 pages
File Size : 49,9 Mb
Release : 1992
Category : Expert systems
ISBN : 9051990820

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Fuzzy Engineering Toward Human Friendly Systems by Toshiro Terano Pdf

Comprising papers presented at an international symposium on fuzzy engineering technology, this volume provides information on the current state-of-the-art in the field of fuzzy theories and applications, and their importance in the areas of industry, medicine, artificial intelligence, management, socio-economics, ecology, agriculture, behavioural science and education. The results of recent research of LIFE (Laboratory for International Fuzzy Engineering Research) are also included.

Introduction to Pattern Recognition and Machine Learning

M Narasimha Murty,V Susheela Devi
Introduction to Pattern Recognition and Machine Learning Book PDF

Author : M Narasimha Murty,V Susheela Devi
Publisher : World Scientific
Page : 404 pages
File Size : 43,9 Mb
Release : 2015-04-22
Category : Computers
ISBN : 9789814656276

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Introduction to Pattern Recognition and Machine Learning by M Narasimha Murty,V Susheela Devi Pdf

This book adopts a detailed and methodological algorithmic approach to explain the concepts of pattern recognition. While the text provides a systematic account of its major topics such as pattern representation and nearest neighbour based classifiers, current topics — neural networks, support vector machines and decision trees — attributed to the recent vast progress in this field are also dealt with. Introduction to Pattern Recognition and Machine Learning will equip readers, especially senior computer science undergraduates, with a deeper understanding of the subject matter. Contents:IntroductionTypes of DataFeature Extraction and Feature SelectionBayesian LearningClassificationClassification Using Soft Computing TechniquesData ClusteringSoft ClusteringApplication — Social and Information Networks Readership: Academics and working professionals in computer science. Key Features:The algorithmic approach taken and the practical issues dealt with will aid the reader in writing programs and implementing methodsCovers recent and advanced topics by providing working exercises, examples and illustrations in each chapterProvides the reader with a deeper understanding of the subject matterKeywords:Clustering;Classification;Supervised Learning;Soft Computing

Pattern Recognition and Data Mining

Sameer Singh,Maneesha Singh,Chid Apte,Petra Perner
Pattern Recognition and Data Mining Book PDF

Author : Sameer Singh,Maneesha Singh,Chid Apte,Petra Perner
Publisher : Springer Science & Business Media
Page : 713 pages
File Size : 53,5 Mb
Release : 2005-08-18
Category : Computers
ISBN : 9783540287575

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Pattern Recognition and Data Mining by Sameer Singh,Maneesha Singh,Chid Apte,Petra Perner Pdf

The two volume set LNCS 3686 and LNCS 3687 constitutes the refereed proceedings of the Third International Conference on Advances in Pattern Recognition, ICAPR 2005, held in Bath, UK in August 2005. The papers submitted to ICAPR 2005 were thoroughly reviewed by up to three referees per paper and less than 40% of the submitted papers were accepted. The first volume includes 73 contributions related to Pattern Recognition and Data Mining (which included papers from the tracks of pattern recognition methods, knowledge and learning, and data mining); topics addressed are pattern recognition, data mining, signal processing and OCR/ document analysis. The second volume contains 87 contributions related to Pattern Recognition and Image Analysis (which included papers from the applications track) and deals with security and surveillance, biometrics, image processing and medical imaging. It also contains papers from the Workshop on Pattern Recognition for Crime Prevention.

Time Series Analysis

Chun-Kit Ngan
Time Series Analysis Book PDF

Author : Chun-Kit Ngan
Publisher : BoD – Books on Demand
Page : 131 pages
File Size : 53,9 Mb
Release : 2019-11-06
Category : Mathematics
ISBN : 9781789847789

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Time Series Analysis by Chun-Kit Ngan Pdf

This book aims to provide readers with the current information, developments, and trends in a time series analysis, particularly in time series data patterns, technical methodologies, and real-world applications. This book is divided into three sections and each section includes two chapters. Section 1 discusses analyzing multivariate and fuzzy time series. Section 2 focuses on developing deep neural networks for time series forecasting and classification. Section 3 describes solving real-world domain-specific problems using time series techniques. The concepts and techniques contained in this book cover topics in time series research that will be of interest to students, researchers, practitioners, and professors in time series forecasting and classification, data analytics, machine learning, deep learning, and artificial intelligence.

Deep Learning for Time Series Forecasting

Jason Brownlee
Deep Learning for Time Series Forecasting Book PDF

Author : Jason Brownlee
Publisher : Machine Learning Mastery
Page : 572 pages
File Size : 45,6 Mb
Release : 2018-08-30
Category : Computers
ISBN : 8210379456XXX

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Deep Learning for Time Series Forecasting by Jason Brownlee Pdf

Deep learning methods offer a lot of promise for time series forecasting, such as the automatic learning of temporal dependence and the automatic handling of temporal structures like trends and seasonality. With clear explanations, standard Python libraries, and step-by-step tutorial lessons you’ll discover how to develop deep learning models for your own time series forecasting projects.

Data Classification

Charu C. Aggarwal
Data Classification Book PDF

Author : Charu C. Aggarwal
Publisher : CRC Press
Page : 710 pages
File Size : 54,8 Mb
Release : 2014-07-25
Category : Business & Economics
ISBN : 9781466586741

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Data Classification by Charu C. Aggarwal Pdf

Comprehensive Coverage of the Entire Area of Classification Research on the problem of classification tends to be fragmented across such areas as pattern recognition, database, data mining, and machine learning. Addressing the work of these different communities in a unified way, Data Classification: Algorithms and Applications explores the underlying algorithms of classification as well as applications of classification in a variety of problem domains, including text, multimedia, social network, and biological data. This comprehensive book focuses on three primary aspects of data classification: Methods-The book first describes common techniques used for classification, including probabilistic methods, decision trees, rule-based methods, instance-based methods, support vector machine methods, and neural networks. Domains-The book then examines specific methods used for data domains such as multimedia, text, time-series, network, discrete sequence, and uncertain data. It also covers large data sets and data streams due to the recent importance of the big data paradigm. Variations-The book concludes with insight on variations of the classification process. It discusses ensembles, rare-class learning, distance function learning, active learning, visual learning, transfer learning, and semi-supervised learning as well as evaluation aspects of classifiers.

Pattern Recognition and Artificial Intelligence

Mounîm El Yacoubi,Eric Granger,Pong Chi Yuen,Umapada Pal,Nicole Vincent
Pattern Recognition and Artificial Intelligence Book PDF

Author : Mounîm El Yacoubi,Eric Granger,Pong Chi Yuen,Umapada Pal,Nicole Vincent
Publisher : Springer Nature
Page : 537 pages
File Size : 52,5 Mb
Release : 2022-05-28
Category : Computers
ISBN : 9783031092824

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Pattern Recognition and Artificial Intelligence by Mounîm El Yacoubi,Eric Granger,Pong Chi Yuen,Umapada Pal,Nicole Vincent Pdf

This two-volume set constitutes the proceedings of the Third International Conference on Pattern Recognition and Artificial Intelligence, ICPRAI 2022, which took place in Paris, France, in June 2022. The 98 full papers presented were carefully reviewed and selected from 192 submissions. The papers present new advances in the field of pattern recognition and artificial intelligence. They are organized in topical sections as follows: pattern recognition; computer vision; artificial intelligence; big data.

Data Complexity in Pattern Recognition

Mitra Basu,Tin Kam Ho
Data Complexity in Pattern Recognition Book PDF

Author : Mitra Basu,Tin Kam Ho
Publisher : Springer Science & Business Media
Page : 309 pages
File Size : 52,8 Mb
Release : 2006-12-22
Category : Computers
ISBN : 9781846281723

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Data Complexity in Pattern Recognition by Mitra Basu,Tin Kam Ho Pdf

Automatic pattern recognition has uses in science and engineering, social sciences and finance. This book examines data complexity and its role in shaping theory and techniques across many disciplines, probing strengths and deficiencies of current classification techniques, and the algorithms that drive them. The book offers guidance on choosing pattern recognition classification techniques, and helps the reader set expectations for classification performance.

Machine Learning and Data Mining in Pattern Recognition

Petra Perner
Machine Learning and Data Mining in Pattern Recognition Book PDF

Author : Petra Perner
Publisher : Springer
Page : 536 pages
File Size : 51,6 Mb
Release : 2014-07-17
Category : Computers
ISBN : 9783319089799

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Machine Learning and Data Mining in Pattern Recognition by Petra Perner Pdf

This book constitutes the refereed proceedings of the 10th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2014, held in St. Petersburg, Russia in July 2014. The 40 full papers presented were carefully reviewed and selected from 128 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining.

Pattern Recognition

Axel Pinz,Thomas Pock,Horst Bischof,Franz Leberl
Pattern Recognition Book PDF

Author : Axel Pinz,Thomas Pock,Horst Bischof,Franz Leberl
Publisher : Springer
Page : 510 pages
File Size : 51,6 Mb
Release : 2012-08-14
Category : Computers
ISBN : 9783642327179

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Pattern Recognition by Axel Pinz,Thomas Pock,Horst Bischof,Franz Leberl Pdf

This book constitutes the refereed proceedings of the 34th Symposium of the German Association for Pattern Recognition, DAGM 2012, and the 36th Symposium of the Austrian Association for Pattern Recognition, OAGM 2012, held in Graz, Austria, in August 2012. The 27 revised full papers and 23 revised poster papers were carefully reviewed and selected from 98 submissions. The papers are organized in topical sections on segmentation, low-level vision, 3D reconstruction, recognition, applications, learning, and features.

Progress in Pattern Recognition, Image Analysis and Applications

José Francisco Martínez-Trinidad,Jesús Ariel Carrasco Ochoa,Josef Kittler
Progress in Pattern Recognition Image Analysis and Applications Book PDF

Author : José Francisco Martínez-Trinidad,Jesús Ariel Carrasco Ochoa,Josef Kittler
Publisher : Springer
Page : 995 pages
File Size : 54,5 Mb
Release : 2006-10-14
Category : Computers
ISBN : 9783540465577

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Progress in Pattern Recognition, Image Analysis and Applications by José Francisco Martínez-Trinidad,Jesús Ariel Carrasco Ochoa,Josef Kittler Pdf

This book constitutes the refereed proceedings of the 11th Iberoamerican Congress on Pattern Recognition, CIARP 2006, held in Cancun, Mexico in November 2006. The 99 revised full papers presented together with three keynote articles were carefully reviewed and selected from 239 submissions. The papers cover ongoing research and mathematical methods.