MARC details
000 -LEADER |
fixed length control field |
02502cam a2200313 a 4500 |
003 - CONTROL NUMBER IDENTIFIER |
control field |
EG-GiCUC |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
211020s2021 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 |
Ph.D |
099 ## - LOCAL FREE-TEXT CALL NUMBER (OCLC) |
Classification number |
Cai01.18.04.Ph.D.2021.Ab.C |
100 0# - MAIN ENTRY--PERSONAL NAME |
Personal name |
Abdallah Salman Mohammed Aldirawi |
245 12 - TITLE STATEMENT |
Title |
A comparison between classification statistical models and neural networks with application on palestine data / |
Statement of responsibility, etc. |
Abdallah Salman Mohammed Aldirawi ; Supervised Amani Moussa Mohamed , Mahmoud A. Abdelfattah |
246 15 - VARYING FORM OF TITLE |
Title proper/short title |
مقارنة بين نماذج التصنيف الإحصائية والشبكات العصبية مع التطبيق على بيانات من فلسطين |
260 ## - PUBLICATION, DISTRIBUTION, ETC. |
Place of publication, distribution, etc. |
Cairo : |
Name of publisher, distributor, etc. |
Abdallah Salman Mohammed Aldirawi , |
Date of publication, distribution, etc. |
2021 |
300 ## - PHYSICAL DESCRIPTION |
Extent |
125 Leaves : |
Other physical details |
charts ; |
Dimensions |
30cm |
502 ## - DISSERTATION NOTE |
Dissertation note |
Thesis (Ph.D.) - Cairo University - Faculty of Graduate Studies for Statistical Research - Department of Statistics and Econometrics |
520 ## - SUMMARY, ETC. |
Summary, etc. |
This study aims at choosing the best statistical model for Labor Force data in Palestine in 2019, comparing between Multinomial Logistic Regression, Discriminant Analysis and Artificial Neural Networks. The Palestinian Labor Force data has 12 variables with manpower as the dependent variable containing three categories of Employment, Unemployment, and Outside of labor force.The other 11 are all nominal independent variables with the exception of age which is a scale variable. The results of these comparisons have shown that Multinomial Logistic Regression gave the best accuracy in prediction with (82.2%), (79.2%) for Discriminant Analysis and (81.6%) for Artificial Neural Networks. Labor Force data from a survey on Labor Force data with 9 variables have further been used, the dependent variable being nominal with two categories (Employed and Unemployed) while the other 8 independent variables are all nominal except, age variable.The results of these comparisons have shown that Artificial Neural Networks gave the best accuracy in prediction with (82.7%), (81.6%) for Logistic Regression and (79.5%) Discriminant Analysis |
530 ## - ADDITIONAL PHYSICAL FORM AVAILABLE NOTE |
Additional physical form available note |
Issued also as CD |
653 #4 - INDEX TERM--UNCONTROLLED |
Uncontrolled term |
Artificial Neural Networks |
653 #4 - INDEX TERM--UNCONTROLLED |
Uncontrolled term |
Discriminant Analysis |
653 #4 - INDEX TERM--UNCONTROLLED |
Uncontrolled term |
Multinomial Logistic Regression |
700 0# - ADDED ENTRY--PERSONAL NAME |
Personal name |
Amani Moussa Mohamed , |
Relator term |
|
700 0# - ADDED ENTRY--PERSONAL NAME |
Personal name |
Mahmoud A. Abdelfattah , |
Relator term |
|
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 |