Contemporary Perspectives in Data Mining

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Release : 2021-01-01
Genre : Computers
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Book Rating : 45X/5 ( reviews)

Contemporary Perspectives in Data Mining - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Contemporary Perspectives in Data Mining write by Kenneth D. Lawrence. This book was released on 2021-01-01. Contemporary Perspectives in Data Mining available in PDF, EPUB and Kindle. The series, Contemporary Perspectives on Data Mining, is composed of blind refereed scholarly research methods and applications of data mining. This series will be targeted both at the academic community, as well as the business practitioner. Data mining seeks to discover knowledge from vast amounts of data with the use of statistical and mathematical techniques. The knowledge is extracted from this data by examining the patterns of the data, whether they be associations of groups or things, predictions, sequential relationships between time order events or natural groups. Data mining applications are in business (banking, brokerage, and insurance), marketing (customer relationship, retailing, logistics, and travel), as well as in manufacturing, health care, fraud detection, homeland security and law enforcement.

Contemporary Perspectives in Data Mining, Volume 1

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Release : 2013-04-01
Genre : Mathematics
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Book Rating : 576/5 ( reviews)

Contemporary Perspectives in Data Mining, Volume 1 - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Contemporary Perspectives in Data Mining, Volume 1 write by Kenneth D. Lawrence. This book was released on 2013-04-01. Contemporary Perspectives in Data Mining, Volume 1 available in PDF, EPUB and Kindle. The series, Contemporary Perspectives on Data Mining, is composed of blind refereed scholarly research methods and applications of data mining. This series will be targeted both at the academic community, as well as the business practitioner. Data mining seeks to discover knowledge from vast amounts of data with the use of statistical and mathematical techniques. The knowledge is extracted form this data by examining the patterns of the data, whether they be associations of groups or things, predictions, sequential relationships between time order events or natural groups. Data mining applications are seen in finance (banking, brokerage, insurance), marketing (customer relationships, retailing, logistics, travel), as well as in manufacturing, health care, fraud detection, home-land security, and law enforcement.

Contemporary Perspectives in Data Mining, Volume 2

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Release : 2015-07-01
Genre : Mathematics
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Book Rating : 895/5 ( reviews)

Contemporary Perspectives in Data Mining, Volume 2 - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Contemporary Perspectives in Data Mining, Volume 2 write by Kenneth D. Lawrence. This book was released on 2015-07-01. Contemporary Perspectives in Data Mining, Volume 2 available in PDF, EPUB and Kindle. The series, Contemporary Perspectives on Data Mining, is composed of blind refereed scholarly research methods and applications of data mining. This series will be targeted both at the academic community, as well as the business practitioner. Data mining seeks to discover knowledge from vast amounts of data with the use of statistical and mathematical techniques. The knowledge is extracted from this data by examining the patterns of the data, whether they be associations of groups or things, predictions, sequential relationships between time order events or natural groups. Data mining applications are in marketing (customer loyalty, identifying profitable customers, instore promotions, e-commerce populations); in business (teaching data mining, efficiency of the Chinese automobile industry, moderate asset allocation funds); and techniques (veterinary predictive models, data integrity in the cloud, irregular pattern detection in a mobility network and road safety modeling.)

Contemporary Perspectives in Data Mining

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Release : 2017-09-01
Genre : Computers
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Book Rating : 563/5 ( reviews)

Contemporary Perspectives in Data Mining - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Contemporary Perspectives in Data Mining write by Kenneth D. Lawrence. This book was released on 2017-09-01. Contemporary Perspectives in Data Mining available in PDF, EPUB and Kindle. The series, Contemporary Perspectives on Data Mining, is composed of blind refereed scholarly research methods and applications of data mining. This series will be targeted both at the academic community, as well as the business practitioner. Data mining seeks to discover knowledge from vast amounts of data with the use of statistical and mathematical techniques. The knowledge is extracted from this data by examining the patterns of the data, whether they be associations of groups or things, predictions, sequential relationships between time order events or natural groups. Data mining applications are in finance (banking, brokerage, and insurance), marketing (customer relationships, retailing, logistics, and travel), as well as in manufacturing, health care, fraud detection, homeland security, and law enforcement.

Data Mining

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Release : 2011-02-03
Genre : Computers
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Book Rating : 369/5 ( reviews)

Data Mining - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Data Mining write by Ian H. Witten. This book was released on 2011-02-03. Data Mining available in PDF, EPUB and Kindle. Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including new material on Data Transformations, Ensemble Learning, Massive Data Sets, Multi-instance Learning, plus a new version of the popular Weka machine learning software developed by the authors. Witten, Frank, and Hall include both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. The book is targeted at information systems practitioners, programmers, consultants, developers, information technology managers, specification writers, data analysts, data modelers, database R&D professionals, data warehouse engineers, data mining professionals. The book will also be useful for professors and students of upper-level undergraduate and graduate-level data mining and machine learning courses who want to incorporate data mining as part of their data management knowledge base and expertise. Provides a thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques to your data mining projects Offers concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods Includes downloadable Weka software toolkit, a collection of machine learning algorithms for data mining tasks—in an updated, interactive interface. Algorithms in toolkit cover: data pre-processing, classification, regression, clustering, association rules, visualization