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Visual Data Mining

2002-09-18 Computers
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Release : 2002-09-18
Genre : Computers
Kind : eBook
Book Rating : 381/5 ( reviews)

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Book Synopsis Visual Data Mining by : Tom Soukup

Download or read book Visual Data Mining written by Tom Soukup. This book was released on 2002-09-18. Available in PDF, EPUB and Kindle. Book excerpt: Marketing analysts use data mining techniques to gain a reliable understanding of customer buying habits and then use that information to develop new marketing campaigns and products. Visual mining tools introduce a world of possibilities to a much broader and non-technical audience to help them solve common business problems. Explains how to select the appropriate data sets for analysis, transform the data sets into usable formats, and verify that the sets are error-free Reviews how to choose the right model for the specific type of analysis project, how to analyze the model, and present the results for decision making Shows how to solve numerous business problems by applying various tools and techniques Companion Web site offers links to data visualization and visual data mining tools, and real-world success stories using visual data mining

Visual Data Mining

2008-07-18 Computers
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Release : 2008-07-18
Genre : Computers
Kind : eBook
Book Rating : 795/5 ( reviews)

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Book Synopsis Visual Data Mining by : Simeon Simoff

Download or read book Visual Data Mining written by Simeon Simoff. This book was released on 2008-07-18. Available in PDF, EPUB and Kindle. Book excerpt: The importance of visual data mining, as a strong sub-discipline of data mining, had already been recognized in the beginning of the decade. In 2005 a panel of renowned individuals met to address the shortcomings and drawbacks of the current state of visual information processing. The need for a systematic and methodological development of visual analytics was detected. This book aims at addressing this need. Through a collection of 21 contributions selected from more than 46 submissions, it offers a systematic presentation of the state of the art in the field. The volume is structured in three parts on theory and methodologies, techniques, and tools and applications.

Visual Data Mining

2012-10-17 Mathematics
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Release : 2012-10-17
Genre : Mathematics
Kind : eBook
Book Rating : 252/5 ( reviews)

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Book Synopsis Visual Data Mining by : Russell K. Anderson

Download or read book Visual Data Mining written by Russell K. Anderson. This book was released on 2012-10-17. Available in PDF, EPUB and Kindle. Book excerpt: A visual approach to data mining. Data mining has been defined as the search for useful and previously unknown patterns in large datasets, yet when faced with the task of mining a large dataset, it is not always obvious where to start and how to proceed. This book introduces a visual methodology for data mining demonstrating the application of methodology along with a sequence of exercises using VisMiner. VisMiner has been developed by the author and provides a powerful visual data mining tool enabling the reader to see the data that they are working on and to visually evaluate the models created from the data. Key features: Presents visual support for all phases of data mining including dataset preparation. Provides a comprehensive set of non-trivial datasets and problems with accompanying software. Features 3-D visualizations of multi-dimensional datasets. Gives support for spatial data analysis with GIS like features. Describes data mining algorithms with guidance on when and how to use. Accompanied by VisMiner, a visual software tool for data mining, developed specifically to bridge the gap between theory and practice. Visual Data Mining: The VisMiner Approach is designed as a hands-on work book to introduce the methodologies to students in data mining, advanced statistics, and business intelligence courses. This book provides a set of tutorials, exercises, and case studies that support students in learning data mining processes. In praise of the VisMiner approach: "What we discovered among students was that the visualization concepts and tools brought the analysis alive in a way that was broadly understood and could be used to make sound decisions with greater certainty about the outcomes" —Dr. James V. Hansen, J. Owen Cherrington Professor, Marriott School, Brigham Young University, USA "Students learn best when they are able to visualize relationships between data and results during the data mining process. VisMiner is easy to learn and yet offers great visualization capabilities throughout the data mining process. My students liked it very much and so did I." —Dr. Douglas Dean, Assoc. Professor of Information Systems, Marriott School, Brigham Young University, USA

Information Visualization in Data Mining and Knowledge Discovery

2002 Computers
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Release : 2002
Genre : Computers
Kind : eBook
Book Rating : 890/5 ( reviews)

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Book Synopsis Information Visualization in Data Mining and Knowledge Discovery by : Usama M. Fayyad

Download or read book Information Visualization in Data Mining and Knowledge Discovery written by Usama M. Fayyad. This book was released on 2002. Available in PDF, EPUB and Kindle. Book excerpt: This text surveys research from the fields of data mining and information visualisation and presents a case for techniques by which information visualisation can be used to uncover real knowledge hidden away in large databases.

Data Mining and Data Visualization

2005-05-02 Mathematics
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Release : 2005-05-02
Genre : Mathematics
Kind : eBook
Book Rating : 404/5 ( reviews)

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Book Synopsis Data Mining and Data Visualization by :

Download or read book Data Mining and Data Visualization written by . This book was released on 2005-05-02. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining and Data Visualization focuses on dealing with large-scale data, a field commonly referred to as data mining. The book is divided into three sections. The first deals with an introduction to statistical aspects of data mining and machine learning and includes applications to text analysis, computer intrusion detection, and hiding of information in digital files. The second section focuses on a variety of statistical methodologies that have proven to be effective in data mining applications. These include clustering, classification, multivariate density estimation, tree-based methods, pattern recognition, outlier detection, genetic algorithms, and dimensionality reduction. The third section focuses on data visualization and covers issues of visualization of high-dimensional data, novel graphical techniques with a focus on human factors, interactive graphics, and data visualization using virtual reality. This book represents a thorough cross section of internationally renowned thinkers who are inventing methods for dealing with a new data paradigm. Distinguished contributors who are international experts in aspects of data mining Includes data mining approaches to non-numerical data mining including text data, Internet traffic data, and geographic data Highly topical discussions reflecting current thinking on contemporary technical issues, e.g. streaming data Discusses taxonomy of dataset sizes, computational complexity, and scalability usually ignored in most discussions Thorough discussion of data visualization issues blending statistical, human factors, and computational insights

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