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A recommender tool for classification algorithms / (Record no. 80392)

MARC details
000 -LEADER
fixed length control field 03038cam a2200337 a 4500
003 - CONTROL NUMBER IDENTIFIER
control field EG-GiCUC
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250223032720.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 210327s2020 ua d f m 000 0 eng d
040 ## - CATALOGING SOURCE
Original cataloging agency EG-GiCUC
Language of cataloging eng
Transcribing agency EG-GiCUC
041 0# - LANGUAGE CODE
Language code of text/sound track or separate title eng
049 ## - LOCAL HOLDINGS (OCLC)
Holding library Deposite
097 ## - Thesis Degree
Thesis Level M.Sc
099 ## - LOCAL FREE-TEXT CALL NUMBER (OCLC)
Classification number Cai01.20.03.M.Sc.2020.Ma.R
100 0# - MAIN ENTRY--PERSONAL NAME
Personal name Mariam Moustafa Reda Abdallah Eltantawi
245 12 - TITLE STATEMENT
Title A recommender tool for classification algorithms /
Statement of responsibility, etc. Mariam Moustafa Reda Abdallah Eltantawi ; Supervised Akram Salah , Mohammed Nassef
246 15 - VARYING FORM OF TITLE
Title proper/short title أداة تزكية للخوارزميات التصنيفية
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Cairo :
Name of publisher, distributor, etc. Mariam Moustafa Reda Abdallah Eltantawi ,
Date of publication, distribution, etc. 2020
300 ## - PHYSICAL DESCRIPTION
Extent 104 Leaves :
Other physical details charts ;
Dimensions 30cm
502 ## - DISSERTATION NOTE
Dissertation note Thesis (M.Sc.) - Cairo University - Faculty of Computers and Artificial Intelligence - Department of Computer Science
520 ## - SUMMARY, ETC.
Summary, etc. In the process of selecting the most appropriate classification algorithm, there are two main tasks. The determination of the factors that will be used in the selection process and the methodology that will be used to make use of these factors and decide upon the most appropriate algorithm to solve the problem. The first task is to characterize datasets; by extracting its characteristics/meta-data or by adopting a reasonable characterization approach, whilst the second task is the learning and deciding task based on the characterization. Choosing the most appropriate classification algorithm for classification problem is becoming a strategically important task in the data-mining process. Due to the availability of numerous classification algorithms in the area of data mining for solving the same kind of problem, with little guidance available for recommending the most appropriate algorithm to use which gives best results for the dataset at hand, this task becomes more and more complicated. As a way of optimizing the chances of recommending the most appropriate classification algorithm for a dataset, a two-step study was conducted: (1) Survey study focusing on the different factors considered by data miners and researchers in different studies when manually selecting the classification algorithms that will yield desired knowledge for the dataset at hand, a categorization tree was created for the measurable factors.The categorization tree, groups and categorizes these factors so that they can be exploited by recommendation software tools. (2) Experimental study of an automated tool based on a pure Collaborative Filtering Recommender System, User-Item approach, to recommend the most appropriate classification algorithm for a classification problem, relying on historical datasets meta-data
530 ## - ADDITIONAL PHYSICAL FORM AVAILABLE NOTE
Additional physical form available note Issued also as CD
653 #4 - INDEX TERM--UNCONTROLLED
Uncontrolled term Algorithm selection
653 #4 - INDEX TERM--UNCONTROLLED
Uncontrolled term Classification
653 #4 - INDEX TERM--UNCONTROLLED
Uncontrolled term Data mining
700 0# - ADDED ENTRY--PERSONAL NAME
Personal name Akram Salah ,
Relator term
700 0# - ADDED ENTRY--PERSONAL NAME
Personal name Mohammed Nassef ,
Relator term
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="http://172.23.153.220/th.pdf">http://172.23.153.220/th.pdf</a>
905 ## - LOCAL DATA ELEMENT E, LDE (RLIN)
Cataloger Nazla
Reviser Revisor
905 ## - LOCAL DATA ELEMENT E, LDE (RLIN)
Cataloger Shimaa
Reviser Cataloger
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Thesis
Holdings
Source of classification or shelving scheme Not for loan Home library Current library Date acquired Full call number Barcode Date last seen Koha item type Copy number
Dewey Decimal Classification   المكتبة المركزبة الجديدة - جامعة القاهرة قاعة الرسائل الجامعية - الدور الاول 11.02.2024 Cai01.20.03.M.Sc.2020.Ma.R 01010110083036000 22.09.2023 Thesis  
Dewey Decimal Classification   المكتبة المركزبة الجديدة - جامعة القاهرة مخـــزن الرســائل الجـــامعية - البدروم 11.02.2024 Cai01.20.03.M.Sc.2020.Ma.R 01020110083036000 22.09.2023 CD - Rom 83036.CD
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