Data Mining: A Tutorial-Based Primer, Second Edition (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)

Richard J. Roiger

  • 出版商: Chapman
  • 出版日期: 2016-12-01
  • 定價: $1,400
  • 售價: 9.8$1,372
  • 語言: 英文
  • 頁數: 529
  • 裝訂: Paperback
  • ISBN: 1498763979
  • ISBN-13: 9781498763974
  • 相關分類: Data-mining
  • 立即出貨(限量) (庫存=3)

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商品描述

Data Mining: A Tutorial-Based Primer, Second Edition provides a comprehensive introduction to data mining with a focus on model building and testing, as well as on interpreting and validating results. The text guides students to understand how data mining can be employed to solve real problems and recognize whether a data mining solution is a feasible alternative for a specific problem. Fundamental data mining strategies, techniques, and evaluation methods are presented and implemented with the help of two well-known software tools.

 Several new topics have been added to the second edition including an introduction to Big Data and data analytics, ROC curves, Pareto lift charts, methods for handling large-sized, streaming and imbalanced data, support vector machines, and extended coverage of textual data mining. The second edition contains tutorials for attribute selection, dealing with imbalanced data, outlier analysis, time series analysis, mining textual data, and more.

 The text provides in-depth coverage of RapidMiner Studio and Weka’s Explorer interface. Both software tools are used for stepping students through the tutorials depicting the knowledge discovery process. This allows the reader maximum flexibility for their hands-on data mining experience.

商品描述(中文翻譯)

《資料探勘:基於教學的入門指南,第二版》提供了一個全面的資料探勘介紹,重點放在模型建立和測試,以及解釋和驗證結果。本書引導學生了解如何運用資料探勘解決實際問題,並判斷資料探勘解決方案是否適用於特定問題。本書介紹了基本的資料探勘策略、技術和評估方法,並借助兩個知名的軟體工具進行實作。

第二版新增了幾個主題,包括大數據和資料分析的介紹、ROC曲線、Pareto提升圖、處理大型、流式和不平衡資料的方法、支持向量機,以及對文字資料探勘的擴展涵蓋。第二版還包含了屬性選擇、處理不平衡資料、異常值分析、時間序列分析、文字資料探勘等教學。

本書詳細介紹了RapidMiner Studio和Weka的Explorer界面。這兩個軟體工具用於引導學生進行教學,展示知識發現過程。這使讀者在實際資料探勘經驗中具有最大的靈活性。

目錄大綱

Section I Data Mining Fundamentals
 1. Data Mining: A First View
 2. Data Mining: A Closer Look
 3. Basic Data Mining Techniques

Section II Tools for Knowledge Discovery
 4. Weka—An Environment for Knowledge Discovery
 5. Knowledge Discovery with RapidMiner
 6. The Knowledge Discovery Process
 7. Formal Evaluation Techniques

Section III Building Neural Networks
 8. Neural Networks
 9. Building Neural Networks with Weka
 10. Building Neural Networks with RapidMiner

Section IV Advanced Data Mining Techniques
 11. Supervised Statistical Techniques
 12. Unsupervised Clustering Techniques
 13. Specialized Techniques
 14. The Data Warehouse

目錄大綱(中文翻譯)

第一節 數據挖掘基礎
1. 數據挖掘:初探
2. 數據挖掘:深入探究
3. 基本數據挖掘技術

第二節 知識發現工具
4. Weka - 知識發現環境
5. 使用RapidMiner進行知識發現
6. 知識發現過程
7. 正式評估技術

第三節 構建神經網絡
8. 神經網絡
9. 使用Weka構建神經網絡
10. 使用RapidMiner構建神經網絡

第四節 高級數據挖掘技術
11. 監督式統計技術
12. 非監督式聚類技術
13. 專業技術
14. 數據倉庫