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Data Mining And Data Visualization


Data Mining And Data Visualization
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Data Mining And Data Visualization


Data Mining And Data Visualization
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Author :
language : en
Publisher: Elsevier
Release Date : 2005-05-02

Data Mining And Data Visualization written by and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-05-02 with Mathematics categories.


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



Visual Data Mining


Visual Data Mining
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Author : Tom Soukup
language : en
Publisher: John Wiley & Sons
Release Date : 2002-09-18

Visual Data Mining written by Tom Soukup and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-09-18 with Computers categories.


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



Modern Data Warehousing Mining And Visualization


Modern Data Warehousing Mining And Visualization
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Author : George M. Marakas
language : en
Publisher:
Release Date : 2003

Modern Data Warehousing Mining And Visualization written by George M. Marakas and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Business & Economics categories.


For undergraduate/graduate-level Data Mining or Data Warehousing courses in Information Systems or Operations Management Departments electives. Taking a multidisciplinary user/manager approach, this text looks at data warehousing technologies necessary to support the business processes of the twenty-first century. Using a balanced professional and conversational approach, it explores the basic concepts of data mining, warehousing, and visualization with an emphasis on both technical and managerial issues and the implication of these modern emerging technologies on those issues. Data mining and visualization exercises using an included fully-enabled, but time-limited version of Megaputer's PolyAnalyst and TextAnalyst data mining and visualization software give students hands-on experience with real-world applications.



Information Visualization In Data Mining And Knowledge Discovery


Information Visualization In Data Mining And Knowledge Discovery
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Author : Usama M. Fayyad
language : en
Publisher: Morgan Kaufmann
Release Date : 2002

Information Visualization In Data Mining And Knowledge Discovery written by Usama M. Fayyad and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Computers categories.


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 Visualization Guide


Data Visualization Guide
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Author : Alex Campbell
language : en
Publisher: Independently Published
Release Date : 2021-01-24

Data Visualization Guide written by Alex Campbell and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-24 with categories.


Have you ever wondered how you can work with large volumes of data sets? Do you ever think about how you can use these data sets to identify hidden patterns and make an informed decision? Do you know where you can collect this information? Have you ever questioned what you can do with incomplete or incorrect data sets? If you said yes to any of these questions, then you have come to the right place. Most businesses collect information from various sources. This information can be in different formats and needs to be collected, processed, and improved upon if you want to interpret it. You can use various data mining tools to source the information from different places. These tools can also help with the cleaning and processing techniques. You can use this information to make informed decisions and improve the efficiency and methods in your business. Every business needs to find a way to interpret and analyze large data sets. To do this, you will need to learn more about the different libraries and functions used to improve data sets. Since most data professionals use Python as the base programming language to develop models, this book uses some common libraries and functions from Python to give you a brief introduction to the language. If you are a budding analyst or want to freshen up on your concepts, this book is for you. It has all the basic information you need to help you become a data analyst or scientist. In this book, you will: Learn what data mining is, and how you can apply in different fields. Discover the different components in data mining architecture. Investigate the different tools used for data mining. Uncover what data analysis is and why it's important. Understand how to prepare for data analysis. Visualize the data. And so much more! So, what are you waiting for? Grab a copy of this book now.



Visual Data Mining


Visual Data Mining
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Author : Simeon Simoff
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-07-18

Visual Data Mining written by Simeon Simoff and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-07-18 with Computers categories.


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.



Making Sense Of Data Ii


Making Sense Of Data Ii
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Author : Glenn J. Myatt
language : en
Publisher: John Wiley & Sons
Release Date : 2009-02-03

Making Sense Of Data Ii written by Glenn J. Myatt and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-02-03 with Mathematics categories.


A hands-on guide to making valuable decisions from data using advanced data mining methods and techniques This second installment in the Making Sense of Data series continues to explore a diverse range of commonly used approaches to making and communicating decisions from data. Delving into more technical topics, this book equips readers with advanced data mining methods that are needed to successfully translate raw data into smart decisions across various fields of research including business, engineering, finance, and the social sciences. Following a comprehensive introduction that details how to define a problem, perform an analysis, and deploy the results, Making Sense of Data II addresses the following key techniques for advanced data analysis: Data Visualization reviews principles and methods for understanding and communicating data through the use of visualization including single variables, the relationship between two or more variables, groupings in data, and dynamic approaches to interacting with data through graphical user interfaces. Clustering outlines common approaches to clustering data sets and provides detailed explanations of methods for determining the distance between observations and procedures for clustering observations. Agglomerative hierarchical clustering, partitioned-based clustering, and fuzzy clustering are also discussed. Predictive Analytics presents a discussion on how to build and assess models, along with a series of predictive analytics that can be used in a variety of situations including principal component analysis, multiple linear regression, discriminate analysis, logistic regression, and Naïve Bayes. Applications demonstrates the current uses of data mining across a wide range of industries and features case studies that illustrate the related applications in real-world scenarios. Each method is discussed within the context of a data mining process including defining the problem and deploying the results, and readers are provided with guidance on when and how each method should be used. The related Web site for the series (www.makingsenseofdata.com) provides a hands-on data analysis and data mining experience. Readers wishing to gain more practical experience will benefit from the tutorial section of the book in conjunction with the TraceisTM software, which is freely available online. With its comprehensive collection of advanced data mining methods coupled with tutorials for applications in a range of fields, Making Sense of Data II is an indispensable book for courses on data analysis and data mining at the upper-undergraduate and graduate levels. It also serves as a valuable reference for researchers and professionals who are interested in learning how to accomplish effective decision making from data and understanding if data analysis and data mining methods could help their organization.



Data Visualization


Data Visualization
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Author : Alex Campbell
language : en
Publisher:
Release Date : 2020

Data Visualization written by Alex Campbell and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Data mining categories.




Innovative Approaches Of Data Visualization And Visual Analytics


Innovative Approaches Of Data Visualization And Visual Analytics
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Author : Huang, Mao Lin
language : en
Publisher: IGI Global
Release Date : 2013-07-31

Innovative Approaches Of Data Visualization And Visual Analytics written by Huang, Mao Lin and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-07-31 with Computers categories.


Due to rapid advances in hardware and software technologies, network infrastructure and data have become increasingly complex, requiring efforts to more effectively comprehend and analyze network topologies and information systems. Innovative Approaches of Data Visualization and Visual Analytics evaluates the latest trends and developments in force-based data visualization techniques, addressing issues in the design, development, evaluation, and application of algorithms and network topologies. This book will assist professionals and researchers working in the fields of data analysis and information science, as well as students in computer science and computer engineering, in developing increasingly effective methods of knowledge creation, management, and preservation.



Data Mining For Business Analytics


Data Mining For Business Analytics
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Author : Galit Shmueli
language : en
Publisher: John Wiley & Sons
Release Date : 2019-10-14

Data Mining For Business Analytics written by Galit Shmueli and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-14 with Mathematics categories.


Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts and methods, using Python software for illustration Readers will learn how to implement a variety of popular data mining algorithms in Python (a free and open-source software) to tackle business problems and opportunities. This is the sixth version of this successful text, and the first using Python. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. It also includes: A new co-author, Peter Gedeck, who brings both experience teaching business analytics courses using Python, and expertise in the application of machine learning methods to the drug-discovery process A new section on ethical issues in data mining Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students More than a dozen case studies demonstrating applications for the data mining techniques described End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology. “This book has by far the most comprehensive review of business analytics methods that I have ever seen, covering everything from classical approaches such as linear and logistic regression, through to modern methods like neural networks, bagging and boosting, and even much more business specific procedures such as social network analysis and text mining. If not the bible, it is at the least a definitive manual on the subject.” —Gareth M. James, University of Southern California and co-author (with Witten, Hastie and Tibshirani) of the best-selling book An Introduction to Statistical Learning, with Applications in R