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Informationen zum Autor Russell K. Anderson , Information & Decision Management Department, West Texas A&M University, USA. Klappentext 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 Zusammenfassung 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 readers to visually evaluate models created from the data. Inhaltsverzeichnis Preface ix Acknowledgments xi 1. Introduction 1 Data Mining Objectives 1 Introduction to VisMiner 2 The Data Mining Process 3 Initial Data Exploration 4 Dataset Preparation 5 Algorithm Selection and Application 8 Model Evaluation 8 Summary 9 2. Initial Data Exploration and Dataset Preparation Using VisMiner 11 The Rationale for Visualizations 11 Tutorial - Using VisMiner 13 Initializing VisMiner 13 Initializing the Slave Computers 14 Opening a Dataset 16 Viewing Summary Statistics 16 Exercise 2.1 17 The Correlation Matrix 18 Exercise 2.2 20 The Histogram 21 The Scatter Plot 23 Exercise 2.3 28 The Parallel Coordinate Plot 28 Exercise 2.4 33 Extracting Sub-populations Using the Parallel Coordinate Plot 37 Exercise 2.5 41 The Table Viewer 42 The Boundary Data Viewer 43 Exercise 2.6 47 The Boundary Data Viewer with Temporal Data 47 Exercise 2.7 49 Summary 49 3. Advanced Topics in Initial Exploration and Dataset Preparation Using VisMiner 51 Missing Values 51 ...
