Learning From Data Streams

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Learning From Data Streams In Evolving Environments

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Author : Moamar Sayed-Mouchaweh
language : en
Publisher: Springer
Release Date : 2018-07-28

Learning From Data Streams In Evolving Environments written by Moamar Sayed-Mouchaweh and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-28 with Technology & Engineering categories.

This edited book covers recent advances of techniques, methods and tools treating the problem of learning from data streams generated by evolving non-stationary processes. The goal is to discuss and overview the advanced techniques, methods and tools that are dedicated to manage, exploit and interpret data streams in non-stationary environments. The book includes the required notions, definitions, and background to understand the problem of learning from data streams in non-stationary environments and synthesizes the state-of-the-art in the domain, discussing advanced aspects and concepts and presenting open problems and future challenges in this field. Provides multiple examples to facilitate the understanding data streams in non-stationary environments; Presents several application cases to show how the methods solve different real world problems; Discusses the links between methods to help stimulate new research and application directions.

Learning From Data Streams

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Author : João Gama
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-10-11

Learning From Data Streams written by João Gama 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 2007-10-11 with Computers categories.

Processing data streams has raised new research challenges over the last few years. This book provides the reader with a comprehensive overview of stream data processing, including famous prototype implementations like the Nile system and the TinyOS operating system. Applications in security, the natural sciences, and education are presented. The huge bibliography offers an excellent starting point for further reading and future research.

Novel Methods For Mining And Learning From Data Streams

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Author : Ammar Shaker
language : en
Publisher:
Release Date : 2017

Novel Methods For Mining And Learning From Data Streams written by Ammar Shaker and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.

In this thesis we elaborate on knowledge acquisition and learning from non-stationary data streams. A data stream is formed by consecutively arriving data examples, whose data generating process may change in the course of time. Both the cumulative and the non-stationary nature of the data within a stream create a challenge for traditional machine learning methods.Concentrating on adaptive supervised learning from data streams, we introduce two novel learning methods: IBLStreams and eFPT. IBLStreams is an instance-based learner that shows how instance-based learning approaches, compared to model-based approaches, are naturally incremental besides their inherent ability to adapt upon the occurrence of a concept change. Evolving fuzzy pattern trees (eFPTs) utilize the potential interpretability of the fuzzy logic concepts in inducing compact trees; the induced trees offer the tradeoff between compact interpretable models and generalization performance. eFPTs attempt to dynamically evolve the induced tree in order to reflect any change in the underlying data generating process.We also introduce "recovery analysis" as a new type of evaluation for adaptive supervised learners on data streams. It is an experimental protocol to assess the learner's ability to learn and recover after a concept change. The resulting recovery pattern of the learning method can be analyzed both graphically and numerically using recovery measures.Apart from the full supervision offered in the streams studied in the previous approaches, we also consider streams of events: such a stream contains temporal events emitted from instances under observation. For a given instance, the survival time is the time this instance spends in the study until experiencing the event of interest. ... ; eng

Learning From Data Streams In Dynamic Environments

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Author : Moamar Sayed-Mouchaweh
language : en
Publisher: Springer
Release Date : 2015-12-10

Learning From Data Streams In Dynamic Environments written by Moamar Sayed-Mouchaweh and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-10 with Technology & Engineering categories.

This book addresses the problems of modeling, prediction, classification, data understanding and processing in non-stationary and unpredictable environments. It presents major and well-known methods and approaches for the design of systems able to learn and to fully adapt its structure and to adjust its parameters according to the changes in their environments. Also presents the problem of learning in non-stationary environments, its interests, its applications and challenges and studies the complementarities and the links between the different methods and techniques of learning in evolving and non-stationary environments.

Learning From Data Streams

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Author : João Gama
language : en
Publisher:
Release Date : 2007

Learning From Data Streams written by João Gama and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Algorithms categories.

Learning From Data Streams With Concept Drift

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Author : Roman Garnett
language : en
Publisher:
Release Date : 2010

Learning From Data Streams With Concept Drift written by Roman Garnett and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.

Knowledge Discovery From Data Streams

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Author : Joao Gama
language : en
Publisher: CRC Press
Release Date : 2010-05-25

Knowledge Discovery From Data Streams written by Joao Gama and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-05-25 with Business & Economics categories.

Since the beginning of the Internet age and the increased use of ubiquitous computing devices, the large volume and continuous flow of distributed data have imposed new constraints on the design of learning algorithms. Exploring how to extract knowledge structures from evolving and time-changing data, Knowledge Discovery from Data Streams presents a coherent overview of state-of-the-art research in learning from data streams. The book covers the fundamentals that are imperative to understanding data streams and describes important applications, such as TCP/IP traffic, GPS data, sensor networks, and customer click streams. It also addresses several challenges of data mining in the future, when stream mining will be at the core of many applications. These challenges involve designing useful and efficient data mining solutions applicable to real-world problems. In the appendix, the author includes examples of publicly available software and online data sets. This practical, up-to-date book focuses on the new requirements of the next generation of data mining. Although the concepts presented in the text are mainly about data streams, they also are valid for different areas of machine learning and data mining.

Learning From Data Streams With Randomized Forests

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Author : T. Seah
language : en
Publisher:
Release Date : 2022

Learning From Data Streams With Randomized Forests written by T. Seah and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.

Learning From Data

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Author : Vladimir S. Cherkassky
language : en
Publisher: Wiley-Interscience
Release Date : 1998-03-25

Learning From Data written by Vladimir S. Cherkassky and has been published by Wiley-Interscience this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-03-25 with Computers categories.

Accommodating both beginning and advanced students, this book establishes a general conceptual framework, in which various learning methods, from statistics, neural networks, and fuzzy logic can be applied--showing that a few fundamental principles underlie most new methods being proposed today in the fields of statistics, engineering, and computer science.

Learning From Data Streams Using Transductive Inference And Martingale

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Author : Shen-Shyang Ho
language : en
Publisher:
Release Date : 2006

Learning From Data Streams Using Transductive Inference And Martingale written by Shen-Shyang Ho and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with categories.