Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.11779/1715
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Özgür Özlük | - |
dc.contributor.author | Sivas, Barış | - |
dc.date.accessioned | 2021-12-14T11:21:15Z | |
dc.date.available | 2021-12-14T11:21:15Z | |
dc.date.issued | 2021 | - |
dc.identifier.citation | Sivas, B. (2021). Employee Performance Prediction. MEF Üniversitesi Fen Bilimleri Enstitüsü, Büyük Veri Analitiği Yüksek Lisans Programı. ss. 1-23 | en_US |
dc.identifier.uri | https://hdl.handle.net/20.500.11779/1715 | - |
dc.description.abstract | DogGo is a company that aims to provide safe and professional dog walking and grooming services to dog owners through the mobile application. Thanks to the DogGo application, dog owners and people who is employee of company and wants to walk their dogs (to be called Walkers) can meet on the same platform on the mobile application interface. The problem was determined by company that they needed to be able to accurately predict the performance of the walkers in the upcoming dog-walker matches, thus ensuring the correct dog walker match. This study will be planned to serve to this company for calculating their current walkers’ performance in an accurate way. The relevant machine-learning model will first be based on the manual scoring system made by the company for the performance of existing employees, and then the model will be developed in the light of the gains obtained from this. For the performance of the model, the employees and their characteristics are important for the first time. | en_US |
dc.language.iso | en | en_US |
dc.publisher | MEF Üniversitesi Fen Bilimleri Enstitüsü | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Performance scoring, Prediction Future Performance, Regression Analysis, Polynomial Features, Ridge, MICE, KNN | en_US |
dc.title | Employee Performance Prediction | en_US |
dc.type | Master's Degree Project | en_US |
dc.relation.publicationcategory | YL-Bitirme Projesi | en_US |
dc.identifier.startpage | 1-23 | en_US |
dc.department | Büyük Veri Analitiği Yüksek Lisans Programı | en_US |
dc.institutionauthor | Sivas, Barış | - |
item.grantfulltext | open | - |
item.fulltext | With Fulltext | - |
item.languageiso639-1 | en | - |
item.openairetype | Master's Degree Project | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
Appears in Collections: | FBE, Yüksek Lisans, Proje Koleksiyonu |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Barış Sivas.pdf | YL-Proje Dosyası | 797.35 kB | Adobe PDF | View/Open |
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