BAZI DENETİMLİ ÖĞRENME ALGORİTMALARININ R PROGRAMLAMA DİLİ İLE KIYASLANMASI.
Artificial intelligence is given to computers' ability to imitate people's thought systems and produce solutions for complex problems. Machine learning is an important subdivision of artificial intelligence. Machine learning can be viewed as a process involving the learning of various tasks and auto...
| Publicado en: | Black Sea / Karadeniz no. 37; pp. 90 - 99 |
|---|---|
| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
Black Sea / Karadeniz
2018
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=129222940&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 129222940 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 13086200 FD1I jtl: Black Sea / Karadeniz issn: 13086200 maglogo: N pubinfo: dt: 2018 iid: 37 pid: 80400 pub: Black Sea / Karadeniz artinfo: ui: 129222940 10.17498/kdeniz.405746 ppf: 90 ppct: 9 formats: tig: atl: BAZI DENETİMLİ ÖĞRENME ALGORİTMALARININ R PROGRAMLAMA DİLİ İLE KIYASLANMASI. aug: au: KIZILKAYA, Yusuf Murat OĞUZLAR, Ayşe affil: Öğr. Gör., Ardahan Üniversitesi SBMYO Prof. Dr., Uludağ Üniversitesi İ.İ.F.B keyword: Logistic Regression Machine Learning R programming Supervised Learning Наивный Байес контролируемого обучения логистическая регрессия машинное обучение программирование на R Denetimli Öğrenme Lojistik Regresyon Makine Öğrenmesi Navie Bayes R Programlama Logistic Regression Machine Learning R programming Supervised Learning Наивный Байес контролируемого обучения логистическая регрессия машинное обучение программирование на R Denetimli Öğrenme Lojistik Regresyon Makine Öğrenmesi Navie Bayes R Programlama ab: Artificial intelligence is given to computers' ability to imitate people's thought systems and produce solutions for complex problems. Machine learning is an important subdivision of artificial intelligence. Machine learning can be viewed as a process involving the learning of various tasks and automatic calculation methods through logical and binary inferences. R programming comes to the forefront with its success in machine learning algorithm as well as many statistical calculations. In this study, the performances of various machine learning algorithms used by R programming for classification purposes are compared. For this purpose, various machine learning algorithms have been applied to real data obtained from UCI Machine Learning Pool and classification algorithms have been compared using several criteria. The calculated criteria are; precision, accuracy, sensitivity, and classification techniques based on the F-measure. As a result of these comparisons, it is seen that Logistic Regulation algorithm, which makes the best classification in the three criteria, is more successful than the other algorithms. The algorithm that has the second best performance of all criteria has been the Navie Bayes algorithm. pubtype: Academic Journal doctype: Article src: R language: Turkish refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
|---|