Adaptive Learning And Mining For Data Streams And Frequent Patterns
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Adaptive Learning And Mining For Data Streams And Frequent Patterns
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Author : Albert Bifet Figuerol
language : en
Publisher:
Release Date : 2009
Adaptive Learning And Mining For Data Streams And Frequent Patterns written by Albert Bifet Figuerol and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with categories.
Adaptive Learning And Mining For Data Streams And Frequent Patterns
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Author : Albert Bifet Figuerol
language : en
Publisher:
Release Date : 2009
Adaptive Learning And Mining For Data Streams And Frequent Patterns written by Albert Bifet Figuerol and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with categories.
Adaptive Stream Mining
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Author : Albert Bifet
language : en
Publisher: IOS Press
Release Date : 2010
Adaptive Stream Mining written by Albert Bifet and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Computers categories.
This book is a significant contribution to the subject of mining time-changing data streams and addresses the design of learning algorithms for this purpose. It introduces new contributions on several different aspects of the problem, identifying research opportunities and increasing the scope for applications. It also includes an in-depth study of stream mining and a theoretical analysis of proposed methods and algorithms. The first section is concerned with the use of an adaptive sliding window algorithm (ADWIN). Since this has rigorous performance guarantees, using it in place of counters or accumulators, it offers the possibility of extending such guarantees to learning and mining algorithms not initially designed for drifting data. Testing with several methods, including Naïve Bayes, clustering, decision trees and ensemble methods, is discussed as well. The second part of the book describes a formal study of connected acyclic graphs, or 'trees', from the point of view of closure-based mining, presenting efficient algorithms for subtree testing and for mining ordered and unordered frequent closed trees. Lastly, a general methodology to identify closed patterns in a data stream is outlined. This is applied to develop an incremental method, a sliding-window based method, and a method that mines closed trees adaptively from data streams. These are used to introduce classification methods for tree data streams.
Machine Learning For Data Streams
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Author : Albert Bifet
language : en
Publisher: MIT Press
Release Date : 2023-05-09
Machine Learning For Data Streams written by Albert Bifet and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-09 with Computers categories.
A hands-on approach to tasks and techniques in data stream mining and real-time analytics, with examples in MOA, a popular freely available open-source software framework. Today many information sources—including sensor networks, financial markets, social networks, and healthcare monitoring—are so-called data streams, arriving sequentially and at high speed. Analysis must take place in real time, with partial data and without the capacity to store the entire data set. This book presents algorithms and techniques used in data stream mining and real-time analytics. Taking a hands-on approach, the book demonstrates the techniques using MOA (Massive Online Analysis), a popular, freely available open-source software framework, allowing readers to try out the techniques after reading the explanations. The book first offers a brief introduction to the topic, covering big data mining, basic methodologies for mining data streams, and a simple example of MOA. More detailed discussions follow, with chapters on sketching techniques, change, classification, ensemble methods, regression, clustering, and frequent pattern mining. Most of these chapters include exercises, an MOA-based lab session, or both. Finally, the book discusses the MOA software, covering the MOA graphical user interface, the command line, use of its API, and the development of new methods within MOA. The book will be an essential reference for readers who want to use data stream mining as a tool, researchers in innovation or data stream mining, and programmers who want to create new algorithms for MOA.
Collaborative Filtering Using Data Mining And Analysis
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Author : Bhatnagar, Vishal
language : en
Publisher: IGI Global
Release Date : 2016-07-13
Collaborative Filtering Using Data Mining And Analysis written by Bhatnagar, Vishal and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-13 with Computers categories.
Internet usage has become a normal and essential aspect of everyday life. Due to the immense amount of information available on the web, it has become obligatory to find ways to sift through and categorize the overload of data while removing redundant material. Collaborative Filtering Using Data Mining and Analysis evaluates the latest patterns and trending topics in the utilization of data mining tools and filtering practices. Featuring emergent research and optimization techniques in the areas of opinion mining, text mining, and sentiment analysis, as well as their various applications, this book is an essential reference source for researchers and engineers interested in collaborative filtering.
Handbook Of Research On Pattern Engineering System Development For Big Data Analytics
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Author : Tiwari, Vivek
language : en
Publisher: IGI Global
Release Date : 2018-04-20
Handbook Of Research On Pattern Engineering System Development For Big Data Analytics written by Tiwari, Vivek and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-20 with Computers categories.
Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries. It is necessary to develop new techniques for managing data in order to ensure adequate usage. The Handbook of Research on Pattern Engineering System Development for Big Data Analytics is a critical scholarly resource that examines the incorporation of pattern management in business technologies as well as decision making and prediction process through the use of data management and analysis. Featuring coverage on a broad range of topics such as business intelligence, feature extraction, and data collection, this publication is geared towards professionals, academicians, practitioners, and researchers seeking current research on the development of pattern management systems for business applications.
Frequent Pattern Mining
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Author : Charu C. Aggarwal
language : en
Publisher: Springer
Release Date : 2014-08-29
Frequent Pattern Mining written by Charu C. Aggarwal and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-29 with Computers categories.
This comprehensive reference consists of 18 chapters from prominent researchers in the field. Each chapter is self-contained, and synthesizes one aspect of frequent pattern mining. An emphasis is placed on simplifying the content, so that students and practitioners can benefit from the book. Each chapter contains a survey describing key research on the topic, a case study and future directions. Key topics include: Pattern Growth Methods, Frequent Pattern Mining in Data Streams, Mining Graph Patterns, Big Data Frequent Pattern Mining, Algorithms for Data Clustering and more. Advanced-level students in computer science, researchers and practitioners from industry will find this book an invaluable reference.
Trends In Applied Knowledge Based Systems And Data Science
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Author : Hamido Fujita
language : en
Publisher: Springer
Release Date : 2016-07-13
Trends In Applied Knowledge Based Systems And Data Science written by Hamido Fujita and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-13 with Computers categories.
This book constitutes the refereed conference proceedings of the 29th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016, held in Morioka, Japan, in August 2-4, 2016. The 80 revised full papers presented were carefully reviewed and selected from 168 submissions. They are organized in topical sections: data science; knowledge base systems; natural language processing and sentiment analysis; semantic Web and social networks; computer vision; medical diagnosis system and bio-informatics; applied neural networks; innovations in intelligent systems and applications; decision support systems; adaptive control; soft computing and multi-agent systems; evolutionary algorithms and heuristic search; system integration for real-life applications.
Computer Vision And Machine Intelligence
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Author : Massimo Tistarelli
language : en
Publisher: Springer Nature
Release Date : 2023-05-05
Computer Vision And Machine Intelligence written by Massimo Tistarelli and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-05 with Technology & Engineering categories.
This book presents selected research papers on current developments in the fields of computer vision and machine intelligence from International Conference on Computer Vision and Machine Intelligence (CVMI 2022). The book covers topics in image processing, artificial intelligence, machine learning, deep learning, computer vision, machine intelligence, etc. The book is useful for researchers, postgraduate and undergraduate students, and professionals working in this domain.
Computational Science Iccs 2021
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Author : Maciej Paszynski
language : en
Publisher: Springer Nature
Release Date : 2021-06-10
Computational Science Iccs 2021 written by Maciej Paszynski and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-10 with Computers categories.
The six-volume set LNCS 12742, 12743, 12744, 12745, 12746, and 12747 constitutes the proceedings of the 21st International Conference on Computational Science, ICCS 2021, held in Krakow, Poland, in June 2021.* The total of 260 full papers and 57 short papers presented in this book set were carefully reviewed and selected from 635 submissions. 48 full and 14 short papers were accepted to the main track from 156 submissions; 212 full and 43 short papers were accepted to the workshops/ thematic tracks from 479 submissions. The papers were organized in topical sections named: Part I: ICCS Main Track Part II: Advances in High-Performance Computational Earth Sciences: Applications and Frameworks; Applications of Computational Methods in Artificial Intelligence and Machine Learning; Artificial Intelligence and High-Performance Computing for Advanced Simulations; Biomedical and Bioinformatics Challenges for Computer Science Part III: Classifier Learning from Difficult Data; Computational Analysis of Complex Social Systems; Computational Collective Intelligence; Computational Health Part IV: Computational Methods for Emerging Problems in (dis-)Information Analysis; Computational Methods in Smart Agriculture; Computational Optimization, Modelling and Simulation; Computational Science in IoT and Smart Systems Part V: Computer Graphics, Image Processing and Artificial Intelligence; Data-Driven Computational Sciences; Machine Learning and Data Assimilation for Dynamical Systems; MeshFree Methods and Radial Basis Functions in Computational Sciences; Multiscale Modelling and Simulation Part VI: Quantum Computing Workshop; Simulations of Flow and Transport: Modeling, Algorithms and Computation; Smart Systems: Bringing Together Computer Vision, Sensor Networks and Machine Learning; Software Engineering for Computational Science; Solving Problems with Uncertainty; Teaching Computational Science; Uncertainty Quantification for Computational Models *The conference was held virtually.