Visual Data Mining: The VisMiner Approach, 2/e (Hardcover)

 

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

「一種視覺化的數據挖掘方法」
數據挖掘被定義為在大型數據集中尋找有用且以前未知的模式，然而當面臨挖掘大型數據集的任務時，往往不清楚應該從哪裡開始和如何進行。

本書介紹了一種視覺化的數據挖掘方法，演示了該方法的應用以及使用VisMiner進行一系列練習。VisMiner是作者開發的一款強大的視覺化數據挖掘工具，讀者可以看到他們正在處理的數據，並對從數據創建的模型進行視覺評估。

主要特點：
- 提供數據挖掘各個階段的視覺支持，包括數據集準備。
- 提供一套包含相應軟件的非平凡數據集和問題。
- 提供多維數據集的三維可視化。
- 支持具有類似GIS功能的空間數據分析。
- 描述數據挖掘算法，並提供何時以及如何使用的指導。
- 附帶VisMiner，一款專門用於數據挖掘的視覺化軟件工具，旨在填補理論與實踐之間的差距。

《視覺化數據挖掘：VisMiner方法》設計為一本實踐手冊，旨在向數據挖掘、高級統計和商業智能課程的學生介紹這些方法。本書提供了一系列教程、練習和案例研究，支持學生學習數據挖掘過程。

對VisMiner方法的讚譽：
「我們在學生中發現，視覺化的概念和工具使分析活躍起來，這種方式被廣泛理解，並且可以用於對結果做出更有把握的決策」- James V. Hansen博士，J. Owen Cherrington教授，Brigham Young University，美國

「學生在能夠在數據挖掘過程中可視化數據和結果之間的關係時學習效果最好。VisMiner易於學習，並且在整個數據挖掘過程中提供了出色的可視化能力。我的學生非常喜歡它，我也是」- Douglas Dean博士，信息系副教授，Brigham Young University，美國