Practical Data Mining
暫譯: 實用資料探勘
Hancock, Jr.
- 出版商: Auerbach Publication
- 出版日期: 2019-09-23
- 售價: $2,830
- 貴賓價: 9.5 折 $2,689
- 語言: 英文
- 頁數: 302
- 裝訂: Quality Paper - also called trade paper
- ISBN: 0367381907
- ISBN-13: 9780367381905
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相關分類:
Data-mining
海外代購書籍(需單獨結帳)
相關主題
商品描述
Used by corporations, industry, and government to inform and fuel everything from focused advertising to homeland security, data mining can be a very useful tool across a wide range of applications. Unfortunately, most books on the subject are designed for the computer scientist and statistical illuminati and leave the reader largely adrift in technical waters.
Revealing the lessons known to the seasoned expert, yet rarely written down for the uninitiated, Practical Data Mining explains the ins-and-outs of the detection, characterization, and exploitation of actionable patterns in data. This working field manual outlines the what, when, why, and how of data mining and offers an easy-to-follow, six-step spiral process. Catering to IT consultants, professional data analysts, and sophisticated data owners, this systematic, yet informal treatment will help readers answer questions, such as:
- What process model should I use to plan and execute a data mining project?
- How is a quantitative business case developed and assessed?
- What are the skills needed for different data mining projects?
- How do I track and evaluate data mining projects?
- How do I choose the best data mining techniques?
Helping you avoid common mistakes, the book describes specific genres of data mining practice. Most chapters contain one or more case studies with detailed projects descriptions, methods used, challenges encountered, and results obtained. The book includes working checklists for each phase of the data mining process. Your passport to successful technical and planning discussions with management, senior scientists, and customers, these checklists lay out the right questions to ask and the right points to make from an insider's point of view.
Visit the book's webpage
商品描述(中文翻譯)
企業、工業和政府使用資料探勘來提供資訊並推動從精準廣告到國土安全等各種應用，資料探勘可以成為一個非常有用的工具。不幸的是，大多數關於這個主題的書籍都是為計算機科學家和統計專家設計的，讓讀者在技術領域中感到迷失。
《實用資料探勘》揭示了資深專家所知的教訓，但這些教訓卻很少為外行人所記錄，該書解釋了在資料中檢測、特徵化和利用可行模式的內部運作。這本工作手冊概述了資料探勘的什麼、何時、為什麼和如何，並提供了一個易於遵循的六步螺旋過程。針對IT顧問、專業資料分析師和高級資料擁有者，這種系統性但非正式的處理方式將幫助讀者回答以下問題：
- 我應該使用什麼流程模型來規劃和執行資料探勘專案？
- 如何開發和評估量化的商業案例？
- 不同資料探勘專案需要哪些技能？
- 我如何追蹤和評估資料探勘專案？
- 我如何選擇最佳的資料探勘技術？
本書幫助您避免常見錯誤，描述了資料探勘實踐的特定類型。大多數章節包含一個或多個案例研究，詳細描述了專案、使用的方法、遇到的挑戰和獲得的結果。本書包括資料探勘過程每個階段的工作檢查清單。這些檢查清單是您與管理層、高級科學家和客戶進行成功技術和規劃討論的通行證，從內部人的角度列出了正確的問題和要點。
訪問本書的網頁。
作者簡介
Monte F. Hancock, Jr., BA, MS, is Chief Scientist for Celestech, Inc., which has offices in Falls Church, Virginia, and Phoenix, Arizona. He was also a Technical Fellow at Northrop Grumman; Chief Cognitive Research Scientist for CSI, Inc., and was a software architect and engineer at Harris corporation, and HRB Singer, Inc. He has over 30 years of industry experience in software engineering and data mining technology development.
He is also Adjunct Full Professor of Computer Science for the Webster University Space Coast Region, where he serves as Program Mentor for the Master of Science Degree in Computer Science. Monte has served for 26 years on the adjunct faculty in the Mathematics and Computer Science Department of the Hamilton Holt School of Rollins College, Winter Park, Florida, and served 3 semesters as adjunct Instructor in Computer Science at Pennsylvania State University.
Monte teaches secondary Mathematics, AP Physics, Chemistry, Logic, Western Philosophy, and Church History at New Covenant School, and New Testament Greek at Heritage Christian Academy, both in Melbourne, Florida. He was a mathematics curriculum developer for the Department of Continuing Education of the University of Florida in Gainesville, and serves on the Industry Advisory Panels in Computer Science for both the Florida Institute of Technology, and Brevard Community College in Melbourne, Florida. Monte has twice served on panels for the National Science Foundation.
Monte has served on many program committees for international data mining conferences, was a Session Chair for KDD. He has presented 15 conference papers, edited several book chapters, and co-authored the book Data Mining Explained with Rhonda Delmater, Digital Press, 2001.
Monte is cited in (among others):
- "Who's Who in the World" (2009-2012)
- "Who's Who in America" (2009-2012)
- "Who's Who in Science and Engineering" (2006-2012)
作者簡介(中文翻譯)
蒙特·F·漢考克（Monte F. Hancock, Jr.），學士、碩士，是Celestech, Inc.的首席科學家，該公司在維吉尼亞州的福爾斯徹奇和亞利桑那州的菲尼克斯設有辦事處。他曾擔任諾斯羅普·格魯曼（Northrop Grumman）的技術研究員；CSI, Inc.的首席認知研究科學家，並在哈里斯公司（Harris Corporation）和HRB辛格公司（HRB Singer, Inc.）擔任軟體架構師和工程師。他在軟體工程和數據挖掘技術開發方面擁有超過30年的行業經驗。
他同時也是韋伯斯特大學（Webster University）太空海岸地區的計算機科學兼任全職教授，並擔任計算機科學碩士學位的課程導師。蒙特在佛羅里達州溫特帕克的羅林斯學院（Rollins College）哈密爾頓·霍爾特學校的數學與計算機科學系擔任兼任教職已有26年，並在賓夕法尼亞州立大學擔任過3學期的計算機科學兼任講師。
蒙特在佛羅里達州梅爾本的新的約定學校（New Covenant School）教授中學數學、AP物理、化學、邏輯、西方哲學和教會歷史，並在遺產基督教學院（Heritage Christian Academy）教授新約希臘文。他曾是佛羅里達大學（University of Florida）持續教育部的數學課程開發者，並在佛羅里達理工學院（Florida Institute of Technology）和佛羅里達州梅爾本的布雷瓦德社區學院（Brevard Community College）擔任計算機科學行業諮詢小組成員。蒙特曾兩次參加國家科學基金會的專家小組。
蒙特曾參與多個國際數據挖掘會議的計畫委員會，並擔任KDD的會議主席。他發表了15篇會議論文，編輯了幾個書章，並與Rhonda Delmater共同撰寫了《數據挖掘解釋》（Data Mining Explained），數位出版社，2001年。
蒙特的著作被引用於（包括但不限於）：
- 《世界名人錄》（Who's Who in the World）（2009-2012）
- 《美國名人錄》（Who's Who in America）（2009-2012）
- 《科學與工程名人錄》（Who's Who in Science and Engineering）（2006-2012）
