Author: Volna, Eva Publisher: IGI Global ISBN: 1522505660 Category : Computers Languages : en Pages : 295
Book Description
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.
Author: Elizabeth Ann Maharaj Publisher: CRC Press ISBN: 0429603304 Category : Mathematics Languages : en Pages : 213
Book Description
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
Author: Horst Bunke Publisher: World Scientific ISBN: 981448654X Category : Computers Languages : en Pages : 205
Book Description
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.
Author: Wladyslaw Homenda Publisher: John Wiley & Sons ISBN: 1119302854 Category : Technology & Engineering Languages : en Pages : 349
Book Description
A new approach to the issue of data quality in pattern recognition Detailing foundational concepts before introducing more complex methodologies and algorithms, this book is a self-contained manual for advanced data analysis and data mining. Top-down organization presents detailed applications only after methodological issues have been mastered, and step-by-step instructions help ensure successful implementation of new processes. By positioning data quality as a factor to be dealt with rather than overcome, the framework provided serves as a valuable, versatile tool in the analysis arsenal. For decades, practical need has inspired intense theoretical and applied research into pattern recognition for numerous and diverse applications. Throughout, the limiting factor and perpetual problem has been data—its sheer diversity, abundance, and variable quality presents the central challenge to pattern recognition innovation. Pattern Recognition: A Quality of Data Perspective repositions that challenge from a hurdle to a given, and presents a new framework for comprehensive data analysis that is designed specifically to accommodate problem data. Designed as both a practical manual and a discussion about the most useful elements of pattern recognition innovation, this book: Details fundamental pattern recognition concepts, including feature space construction, classifiers, rejection, and evaluation Provides a systematic examination of the concepts, design methodology, and algorithms involved in pattern recognition Includes numerous experiments, detailed schemes, and more advanced problems that reinforce complex concepts Acts as a self-contained primer toward advanced solutions, with detailed background and step-by-step processes Introduces the concept of granules and provides a framework for granular computing Pattern recognition plays a pivotal role in data analysis and data mining, fields which are themselves being applied in an expanding sphere of utility. By facing the data quality issue head-on, this book provides students, practitioners, and researchers with a clear way forward amidst the ever-expanding data supply.
Author: Sankar Kumar Pal Publisher: World Scientific ISBN: 9813144564 Category : Computers Languages : en Pages : 875
Book Description
Containing twenty six contributions by experts from all over the world, this book presents both research and review material describing the evolution and recent developments of various pattern recognition methodologies, ranging from statistical, linguistic, fuzzy-set-theoretic, neural, evolutionary computing and rough-set-theoretic to hybrid soft computing, with significant real-life applications.Pattern Recognition and Big Data provides state-of-the-art classical and modern approaches to pattern recognition and mining, with extensive real life applications. The book describes efficient soft and robust machine learning algorithms and granular computing techniques for data mining and knowledge discovery; and the issues associated with handling Big Data. Application domains considered include bioinformatics, cognitive machines (or machine mind developments), biometrics, computer vision, the e-nose, remote sensing and social network analysis.
Author: Charu C. Aggarwal Publisher: CRC Press ISBN: 1466586753 Category : Business & Economics Languages : en Pages : 704
Book Description
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.
Author: Mitra Basu Publisher: Springer Science & Business Media ISBN: 1846281725 Category : Computers Languages : en Pages : 309
Book Description
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.
Author: Sankar K. Pal Publisher: World Scientific ISBN: 9810246846 Category : Computers Languages : en Pages : 635
Book Description
This volume, containing contributions by experts from all over the world, is a collection of 21 articles which present review and research material describing the evolution and recent developments of various pattern recognition methodologies, ranging from statistical, syntactic/linguistic, fuzzy-set-theoretic, neural, genetic-algorithmic and rough-set-theoretic to hybrid soft computing, with significant real-life applications. In addition, the book describes efficient soft machine learning algorithms for data mining and knowledge discovery. With a balanced mixture of theory, algorithms and applications, as well as up-to-date information and an extensive bibliography, Pattern Recognition: From Classical to Modern Approaches is a very useful resource.
Author: Richard O. Duda Publisher: John Wiley & Sons ISBN: 111858600X Category : Technology & Engineering Languages : en Pages : 680
Book Description
The first edition, published in 1973, has become a classicreference in the field. Now with the second edition, readers willfind information on key new topics such as neural networks andstatistical pattern recognition, the theory of machine learning,and the theory of invariances. Also included are worked examples,comparisons between different methods, extensive graphics, expandedexercises and computer project topics. An Instructor's Manual presenting detailed solutions to all theproblems in the book is available from the Wiley editorialdepartment.
Author: Sai Abhishek Devar Publisher: ISBN: Category : Languages : en Pages : 42
Book Description
In this research work, we have implemented machine learning & deep-learning algorithms on realtime multivariate time series datasets in the manufacturing & health care fields. The research work is organized into two case-studies. The case study-1 is about rare event classification in multivariate time series in a pulp and paper manufacturing industry, data was collected of multiple sensors at each stage of the production line, the data contains a rare event of paper break that commonly occurs in the industry. For preprocessing we have implemented a sliding window approach for calculating the first-order difference method to capture the variation in the data over time. The sliding window approach helps to arrange the data for early prediction, for instance, we can set sliding window parameters to predict two or four minutes early as required. Our results indicate that for case study-1 best accuracy score was produced by the TensorFlow deep neural network model it was able to predict 50% of failures and 99% of non-failures with an overall accuracy of 75%. In case study-2 we have brain EEG signal data of patients which were collected with the help of the Stereo EEG Implantation strategy to measure their ability to remember words shown to him/her after distracting him /her with math problems and other activities. The data was collected at a health-care lab at UT-Southwestern Medical Center. The brain EEG signal data collected by the company was preprocessed by using Pearson's and Spearman's correlations, extracting bandwidth frequencies and basic statistics from EEG signal data extracted for each event, event in case study 2 refers to a word shown to a patient. We have used minimum redundancy and maximum relevance feature selection method for dimensionality reduction of the data and to get the most effective features out of all. For case-study 2 best results were produced by SVM-RBF i.e. 73% accuracy to predict if a patient will remember or not remember a word.
Author: Volna, Eva
Author: Elizabeth Ann Maharaj
Author: Horst Bunke
Author: Wladyslaw Homenda
Author: Sankar Kumar Pal
Author: Charu C. Aggarwal
Author: Mitra Basu
Author: Sankar K. Pal
Author: Richard O. Duda
Author: Sai Abhishek Devar