dc.contributor.author |
Atalay, Veli
|
|
dc.contributor.author |
Üstün, Süleyman
|
|
dc.contributor.author |
Bülbül, Selin
|
|
dc.date.accessioned |
2020-04-17T21:02:16Z |
|
dc.date.available |
2020-04-17T21:02:16Z |
|
dc.date.issued |
2013 |
|
dc.identifier.citation |
Atalay, Veli; Ustun, Suleyman; Bulbul, Selin, "The Determination Of Socio-Economic Factors Affecting Student Success By Data Mining Methods", 2013 12th International Conference On Machine Learning and Applıcations (Icmla 2013), pp. 540-542, (2013). |
tr_TR |
dc.identifier.uri |
http://hdl.handle.net/20.500.12416/3300 |
|
dc.description.abstract |
The success of socio-economic level on students is a fact. The economic level and conditions combined with the student's potential make itself felt at the ultimate level. In this research, it was established that success and socio-economic factors which can attract the attention are effectively observed on particularly female students. It was ensured that a real and sound socio-economic criteria for success be determined by evaluating success and failure at terminal points. Decision trees and chi-square test were used in the implementation. |
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dc.language.iso |
eng |
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dc.publisher |
IEEE |
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dc.relation.isversionof |
10.1109/ICMLA.2013.174 |
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dc.rights |
info:eu-repo/semantics/closedAccess |
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dc.subject |
Data Mining |
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dc.subject |
Decision Tree |
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dc.subject |
IBM Moduler |
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dc.subject |
Navie Bayes |
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dc.title |
The Determination of Socio-Economic Factors Affecting Student Success By Data Mining Methods |
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dc.type |
workingPaper |
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dc.relation.journal |
2013 12th International Conference On Machine Learning and Applıcations (Icmla 2013), Vol 2 |
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dc.identifier.startpage |
540 |
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dc.identifier.endpage |
542 |
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dc.contributor.department |
Çankaya Üniversitesi, İktisadi İdari Bilimler Fakültesi, İşletme Bölümü |
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