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Data Mining and Knowledge Discovery With Evolutionary Algorithms

This book integrates two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become;

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Pattern Mining with Evolutionary Algorithms

This book provides a comprehensive overview of the field of pattern mining with evolutionary algorithms. To do so, it covers formal;

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Trends and Applications in Knowledge Discovery and Data Mining

Knowledge Discovery and Data Mining (PAKDD) held in Tainan, Taiwan, in May 2014. The 73 revised papers presented were carefully reviewed and;

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Data Mining Methods for Knowledge Discovery

chapter comes with an extensive bibliography. Data Mining Methods for Knowledge Discovery is intended for senior undergraduate and graduate;

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Hybrid Artificial Intelligent Systems

. They are organized in the following topical sections: data mining, knowledge discovery and big data; bioinspired models and evolutionary;

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Hybrid Artificial Intelligent Systems

. They are organized in the following topical sections: data mining, knowledge discovery and big data; bio-inspired models and evolutionary;

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Data Mining and Knowledge Discovery for Geoscientists

practical applications. Authored by a global thought leader in data mining, Data Mining and Knowledge Discovery for Geoscientists addresses these;

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Advances in Knowledge Discovery and Data Mining

in Knowledge Discovery and Data Mining, PAKDD 2016, held in Auckland, New Zealand, in April 2016. The 91 full papers were carefully reviewed;

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Advances in Knowledge Discovery and Data Mining

in Knowledge Discovery and Data Mining, PAKDD 2016, held in Auckland, New Zealand, in April 2016. The 91 full papers were carefully reviewed;

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Hybrid Artificial Intelligent Systems

in topical sections such as data mining and knowledge discovery; video and image analysis; bio-inspired models and evolutionary computation; learning;

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Service-Oriented Distributed Knowledge Discovery

key areas in data mining and service-oriented computing. It presents the concepts and principles of distributed knowledge discovery and;

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Service-Oriented Distributed Knowledge Discovery

key areas in data mining and service-oriented computing. It presents the concepts and principles of distributed knowledge discovery and;

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Hybrid Artificial Intelligent Systems

submissions. They are organized in topical sections on data mining and knowledge discovery; time series; bio-inspired models and evolutionary;

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Spatiotemporal Frequent Pattern Mining from Evolving Region Trajectories

perspective of relationship modeling among the spatiotemporal objects, frequent pattern mining algorithms, and data access methodologies for mining;

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Advances in Knowledge Discovery and Data Mining

Discovery and Data Mining, PAKDD 2015, held in Ho Chi Minh City, Vietnam, in May 2015. The proceedings contain 117 paper carefully reviewed and;

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Advances in Knowledge Discovery and Data Mining

Discovery and Data Mining, PAKDD 2015, held in Ho Chi Minh City, Vietnam, in May 2015. The proceedings contain 117 paper carefully reviewed and;

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Advances in Knowledge Discovery and Data Mining

in Knowledge Discovery and Data Mining, PAKDD 2017, held in Jeju, South Korea, in May 2017. The 129 full papers were carefully reviewed and selected;

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Advances in Knowledge Discovery and Data Mining

in Knowledge Discovery and Data Mining, PAKDD 2017, held in Jeju, South Korea, in May 2017. The 129 full papers were carefully reviewed and selected;

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New Frontiers in Applied Data Mining

workshopsorganized along with the main 2008 Paci?c Asia Conference on Knowledge Discovery and Data Mining (PAKDD) in Osaka, Japan was to extend the;

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Pattern Recognition And Big Data

, evolutionary computing and rough-set-theoretic to hybrid soft computing, with significant real-life applications.Pattern Recognition and Big Data;

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Pattern Recognition Algorithms for Data Mining

computing in soft frameworks. Organized into eight chapters, the book begins with an introduction to PR, data mining, and knowledge discovery;

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Pattern Recognition Algorithms for Data Mining

computing in soft frameworks. Organized into eight chapters, the book begins with an introduction to PR, data mining, and knowledge discovery;

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Machine Learning and Data Mining

Data mining is often referred to by real-time users and software solutions providers as knowledge discovery in databases (KDD). Good data;

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Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery

the basic concepts and some of the more popular algorithms of data mining. With a focus on the hands-on end-to-end process for data mining;

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Evolutionary Synthesis of Pattern Recognition Systems

in computer vision, pattern recognition, target recognition, machine learning, evolutionary learning, image processing, knowledge discovery and data;

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Advances in Knowledge Discovery and Data Mining

Discovery and Data Mining, PAKDD 2020, which was due to be held in Singapore, in May 2020. The conference was held virtually due to the COVID-19;

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Advances in Knowledge Discovery and Data Mining

Discovery and Data Mining, PAKDD 2020, which was due to be held in Singapore, in May 2020. The conference was held virtually due to the COVID-19;

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