Comparison of Data Mining Algorithms for Emg Signals
| dc.contributor.author | Taşkan Demirkok, Burcu | |
| dc.contributor.author | Elbaşı, Ersin | |
| dc.date.accessioned | 2020-04-15T10:32:29Z | |
| dc.date.available | 2020-04-15T10:32:29Z | |
| dc.date.issued | 2018 | |
| dc.department | Çankaya Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü | en_US |
| dc.description.abstract | The aim of this study is to compare data mining algorithms and having a significant result using selected data mining algorithm on data which was collected during the "The Muscular Activity Analysis of Circumoral and Jaw-Closing Muscles Response To The Trainer on Patients With Class II Malocclusion Using Electromyogram" project. This document gives the accuracy rate of selected data mining algorithms on data set with using WEKA data mining tool. | en_US |
| dc.identifier.citation | Taskan Demirkok, Burcu; Elbasi, Ersin, "Comparison of Data Mining Algorithms for EMG Signals", Icecco'12: 9th International Conference On Electronics, Computer and Computation, pp. 45-48, (2012) | en_US |
| dc.identifier.endpage | 48 | en_US |
| dc.identifier.startpage | 45 | en_US |
| dc.identifier.uri | http://hdl.handle.net/20.500.12416/3138 | |
| dc.language.iso | en | en_US |
| dc.publisher | Turgut Ozal Univ | en_US |
| dc.relation.ispartof | Icecco'12: 9th International Conference On Electronics, Computer and Computation | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | Data Mining | en_US |
| dc.subject | Data Mining Classification Algorithms | en_US |
| dc.subject | Data Mining Clustering Algorithms | en_US |
| dc.subject | EMG Registrations | en_US |
| dc.subject | Herbst and Twin-Block Appliances | en_US |
| dc.subject | WEKA Data Mining Tool | en_US |
| dc.title | Comparison of Data Mining Algorithms for Emg Signals | tr_TR |
| dc.title | Comparison of Data Mining Algorithms for Emg Signals | en_US |
| dspace.entity.type | Publication |
Files
License bundle
1 - 1 of 1
No Thumbnail Available
- Name:
- license.txt
- Size:
- 1.71 KB
- Format:
- Item-specific license agreed upon to submission
- Description: