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Data Mining and Data Warehousing Principles and Practical Techniques

analysis are discussed in detail with their practical implementation using Weka and R language data mining tools. Advanced topics including big;

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Data Warehousing and Knowledge Discovery

tools, data warehouse performance and optimization, pattern mining, matrix-based mining techniques and stream, sensor and time-series mining.;

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Intelligent Data Warehousing

entire process of data warehousing, including data preparation, storage, and mining. Part I provides an overview of the main ideas and;

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Data Mining

Data Mining: Concepts and Techniques, Fourth Edition introduces concepts, principles, and methods for mining patterns, knowledge;

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Data Warehousing with Mining Techniques (22621)

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Professional SQL Server 2000 Data Warehousing with Analysis Services

Mining, Web-Enabled Analysis, and Closed Loop Analysis, plus increased speed, scalability and ease of use.;This book covers: data warehousing and;

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Data Mining Concepts & Techniques

Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be;

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E Governance Data Center, Data Warehousing and Data Mining

Governance Data Center * Perspective Application of Data Warehousing and Data Mining in E Governance * Case Studies on Education and Health Data;

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Big Data Analytics and Knowledge Discovery

. The papers are organized in topical sections on Mining Big Data, Applications of Big Data Mining, Big Data Indexing and Searching, Big Data;

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Data Mining and Knowledge Discovery for Geoscientists

geoscientists have no practical knowledge or experience using data mining techniques. For the few that do, they typically lack expertise in using data;

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Advances on Data Mining: Applications and Theoretical Aspects

in topical sections on data mining in medicine and agriculture, data mining in marketing, data mining for Industrial processes and;

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Advances in Knowledge Discovery and Data Mining

This book constitutes the refereed proceedings of the 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2009, held;

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Data Mining

presents tools and techniques - getting the data ready, carrying out the mining, pruning the results, evaluating outcomes, defining specific;

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Data Mining

presents tools and techniques - getting the data ready, carrying out the mining, pruning the results, evaluating outcomes, defining specific;

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Data Science

, Machine Learning, and Big Data - That You Don't Data Science for Business: Predictive Modeling, Data Mining, Data Analytics, Data Warehousing;

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Advances in Knowledge Discovery and Data Mining

Knowledge Discovery and Data Mining, PAKDD 2019, held in Macau, China, in April 2019. The 137 full papers presented were carefully reviewed;

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Advances in Knowledge Discovery and Data Mining

Knowledge Discovery and Data Mining, PAKDD 2019, held in Macau, China, in April 2019. The 137 full papers presented were carefully reviewed;

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Advances in Knowledge Discovery and Data Mining

Knowledge Discovery and Data Mining, PAKDD 2019, held in Macau, China, in April 2019. The 137 full papers presented were carefully reviewed;

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Advances in Knowledge Discovery and Data Mining

Advances in Knowledge Discovery and Data Mining, PAKDD 2018, held in Melbourne, VIC, Australia, in June 2018. The 164 full papers were;

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Advances in Knowledge Discovery and Data Mining

Advances in Knowledge Discovery and Data Mining, PAKDD 2018, held in Melbourne, VIC, Australia, in June 2018. The 164 full papers were;

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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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Analytical Puzzle

suitable for data mining and analytics. The Analytical Puzzle describes an unbiased, practical, and comprehensive approach to building a data;

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Data Warehousing Essentials

, catalogued, transformed and used for data mining, market research, decision support and online analytical processing. The ways to analyze or retrieve;

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Predictive Analytics and Data Mining

> Predictive analytics and Data Mining techniques covered: Exploratory Data Analysis, Visualization, Decision trees, Rule induction, k-Nearest;

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Advances in Knowledge Discovery and Data Mining

research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning;

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Advances in Knowledge Discovery and Data Mining

research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning;

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Advances in Knowledge Discovery and Data Mining

Data Mining, PAKDD 2011, held in Shenzhen, China in May 2011. The total of 32 revised full papers and 58 revised short papers were carefully;

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