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A novel approach for integrating decision trees, fuzzy sets and rough sets / Mohammed AbouBakr Ibrahim Mohammed Ali Elashiri ; Supervised Ashraf H. Abdelwhab , Hesham A. Hefny

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Mohammed AbouBakr Ibrahim Mohammed Ali Elashiri , 2014Description: 176 Leaves ; 30cmOther title:
  • أسلوب جديد للتكامل بين أشجار القرارات و الفئات المشوشة و الفئات التقريبية [Added title page title]
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  • Issued also as CD
Dissertation note: Thesis (Ph.D.) - Cairo University - Institute of Statistical Studies and Research - Department of Computer and Information sciences Summary: A decision maker is not usually interested in making queries in several thousands of records. However, a decision maker is quite interested to find out that certain hidden patterns that exist and control most of the data stored in the database. Data mining is the powerful scientific approach that can be used to find out such hidden patterns. One of the most famous techniques of data mining is decision trees. Decision trees are widely used for generating trees and extracting a set of - IF THEN - rules, which are quite helpful for making decisions. Classical searching techniques "Traditional decision trees" for a huge database may not be helpful for effective decision making processes. The main serious problem of decision trees is that very large trees may be generated and would added nothing to the process of the decision making
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Item type Current library Home library Call number Copy number Status Date due Barcode
Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.18.02.Ph.D.2014.Mo.N (Browse shelf(Opens below)) Not for loan 01010110064564000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.18.02.Ph.D.2014.Mo.N (Browse shelf(Opens below)) 64564.CD Not for loan 01020110064564000

Thesis (Ph.D.) - Cairo University - Institute of Statistical Studies and Research - Department of Computer and Information sciences

A decision maker is not usually interested in making queries in several thousands of records. However, a decision maker is quite interested to find out that certain hidden patterns that exist and control most of the data stored in the database. Data mining is the powerful scientific approach that can be used to find out such hidden patterns. One of the most famous techniques of data mining is decision trees. Decision trees are widely used for generating trees and extracting a set of - IF THEN - rules, which are quite helpful for making decisions. Classical searching techniques "Traditional decision trees" for a huge database may not be helpful for effective decision making processes. The main serious problem of decision trees is that very large trees may be generated and would added nothing to the process of the decision making

Issued also as CD

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