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Data Mining and Applications in Genomics

provides a systematic introduction to the use of data mining algorithms as an investigative tool for applications in genomics. Data Mining and;

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Data Mining and Applications in Genomics

provides a systematic introduction to the use of data mining algorithms as an investigative tool for applications in genomics. Data Mining and;

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Introduction to Data Mining and its Applications

This book explores the concepts of data mining and data warehousing, a promising and flourishing frontier in database systems, and presents;

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Artificial Intelligence in Data Mining

Artificial Intelligence in Data Mining: Theories and Applications offers a comprehensive introduction to data mining theories, relevant AI;

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Multimedia Data Mining

Collecting the latest developments in the field, Multimedia Data Mining: A Systematic Introduction to Concepts and Theory defines;

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Multimedia Data Mining

Collecting the latest developments in the field, Multimedia Data Mining: A Systematic Introduction to Concepts and Theory defines;

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Data Mining

This book, Data Mining: The Data Mining Guide for Beginners, Including Applications for Business, Data Mining Techniques, Concepts, and;

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Mobile Data Mining and Applications

, from a mobile data mining platform for collecting mobile data, to mobile data processing, and mobile feature discovery. Usage of mobile data;

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Data Mining

Thorough in its coverage from basic to advanced topics, this book presents the key algorithms and techniques used in data mining. An;

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Data Mining

, and scalability of data mining techniques for large data sets. After an introduction to the concept of data mining, the authors;

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Java Data Mining: Strategy, Standard, and Practice

contributors to the JDM standard.Data mining introduction - an overview of data mining and the problems it can address across industries; JDM's;

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Spectral Feature Selection for Data Mining

spectral feature selection, its theoretical foundations, its connections to other algorithms, and its use in handling both large-scale data sets;

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Spectral Feature Selection for Data Mining

spectral feature selection, its theoretical foundations, its connections to other algorithms, and its use in handling both large-scale data sets;

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Domain Driven Data Mining

outputs. This monograph, Domain Driven Data Mining, is motivated by the real-world challenges to and complexities of the current KDD methodologies;

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Advanced Data Mining

This book consists of advanced information regarding data mining and their applications. It offers to aid data miners, researchers;

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Managing Data Mining Technologies in Organizations

Details the state-of-the-art data mining research, which reflects in a potpourri of chapters that demonstrate diverse use of techniques and;

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Real World Data Mining Applications

. In that respect, research at the interface of information systems and data mining has significant potential to produce actionable knowledge vital;

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Advanced Data Mining and Applications

right in the forefront of data mining applications to the world's largest knowledge and data base, the Web, Dr. Chang - scribed how Google's;

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Data Mining and Data Visualization

is divided into three sections. The first deals with an introduction to statistical aspects of data mining and machine learning and includes;

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Querying And Mining Uncertain Data Streams

growth of possible solution space.This book provides a comprehensive overview of the authors' work on querying and mining uncertain data streams;

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Querying And Mining Uncertain Data Streams

growth of possible solution space.This book provides a comprehensive overview of the authors' work on querying and mining uncertain data streams;

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5th International Symposium on Data Mining Applications

The 5th Symposium on Data Mining Applications (SDMA 2018) provides valuable opportunities for technical collaboration among data mining and;

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Data Mining and Knowledge Discovery for Geoscientists

wealth of available mining data amid an absence of the knowledge and expertise necessary to analyze and accurately interpret the same data.Most;

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Data Science Concepts and Techniques with Applications

edition, is devoted to various techniques and tools applied in data science. Its chapters 4 to 10 detail data pre-processing, classification;

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Introduction to Data Mining

Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each major;

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Data Fusion and Data Mining for Power System Monitoring

efficient methods to cluster and visualize data collected from multiple sensors are discussed. Both linear and nonlinear data-driven mining and;

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Data Fusion and Data Mining for Power System Monitoring

efficient methods to cluster and visualize data collected from multiple sensors are discussed. Both linear and nonlinear data-driven mining and;

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