DATA MINING with IBM SPSS MODELER (IBM SPSS CLEMENTINE)

Cesar Perez .

  • 出版商: CreateSpace Independ
  • 出版日期: 2013-06-14
  • 售價: $1,150
  • 貴賓價: 9.5$1,093
  • 語言: 英文
  • 頁數: 242
  • 裝訂: Paperback
  • ISBN: 1490440690
  • ISBN-13: 9781490440699
  • 相關分類: SPSSData-mining
  • 無法訂購

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商品描述

This book presents the most common techniques used in data mining in a simple and easy to understand through one of the most common software solutions from among those existing in the market, in particular, IBM SPSS CLEMENTINE whose current name is IBM SPSS MODELER. Pursued as initial aim clarifying the applications concerning methods traditionally rated as difficult or dull. It seeks to present applications in data mining without having to manage high mathematical developments or complicated theoretical algorithms, which is the most common reason for the difficulties in understanding and implementation of this matter. Today data mining is used in different fields of science. Noteworthy applications in banking, and financial analysis of markets and trade, insurance and private health, in education, in industrial processes, in medicine, biology and bioengineering, telecommunications and in many other areas. Essentials to get started in data mining, regardless of the field in which it is applied, is the understanding of own concepts, task that does not require nor much less the domain of scientific apparatus involved in the matter. Later, when either necessary operative advanced, computer programs allow the results without having to decipher the mathematical development of the algorithms that are under the procedures. This book describes the simplest possible data mining concepts, so that they are understandable by readers with different training. The chapters begin describing the techniques in affordable language and then presenting the way to treat them through practical applications. An important part of each chapter are case studies completely resolved, including the interpretation of the results, which is precisely the most important thing in any matter with which they work. The book begins with an introduction to mining data and its phases. In successive chapters develop the initial phases (selection of information, data exploration, data cleansing, transformation of data, etc.). Subsequently elaborates on specific data mining, both predictive and descriptive techniques. Predictive techniques covers all models of regression, discriminant analysis, decision trees, neural networks and other techniques based on models. The descriptive techniques vary dimension reduction techniques, techniques of classification and segmentation (clustering), and exploratory data analysis techniques.

商品描述(中文翻譯)

這本書介紹了數據挖掘中最常用的技術,通過市場上最常見的軟件解決方案之一,即IBM SPSS CLEMENTINE(現在的名稱是IBM SPSS MODELER),以簡單易懂的方式呈現。它的初衷是澄清傳統上被評為困難或枯燥的方法應用。它旨在呈現數據挖掘的應用,而無需處理高深的數學發展或複雜的理論算法,這是理解和實施這個問題最常見的困難原因。如今,數據挖掘在不同的科學領域中被應用。值得注意的應用包括銀行業、市場和貿易的金融分析、保險和私人健康、教育、工業過程、醫學、生物學和生物工程、電信等許多其他領域。無論應用在哪個領域,開始進行數據挖掘的基本要素是理解相關概念,這不需要掌握與此問題相關的科學設備。稍後,當需要進行高級操作時,計算機程序可以在不需要解讀算法的數學發展的情況下提供結果。本書描述了最簡單的數據挖掘概念,以便讀者能夠理解,無論他們的背景如何。各章節開始以易於理解的語言描述技術,然後通過實際應用介紹處理方法。每個章節的重要部分是完全解決的案例研究,包括對結果的解釋,這正是任何工作中最重要的事情。本書以介紹數據挖掘及其階段開始。在接下來的章節中,發展了初始階段(信息選擇、數據探索、數據清理、數據轉換等)。隨後,對具體的數據挖掘進行了詳細介紹,包括預測和描述性技術。預測技術涵蓋了所有的回歸模型、判別分析、決策樹、神經網絡和其他基於模型的技術。描述性技術包括降維技術、分類和分段(聚類)技術以及探索性數據分析技術。