Metaclassifiers for Predicting the Robotic Navigational Performance
S.Padmapriya1, J.S. Richard Jimreeves2, P. Kalaiselvi3, A. Nageswaran4, S. Arun5
1Dr.S.Padmapriya, Professor, Department of CSE, Prathyusha Engineering College, Chennai, India.
2J.S. Richard Jimreeves, Assistant Professor, Department of IT, Easwari Engineering College, Chennai, India. email-id:
3P. Kalaiselvi, Assistant Professor, Department of CSE, PERI Institute of Technology, Chennai, India.
4Dr.A.Nageswaran, Associate Professor, Department of IT, Kings Engineering College,Irungattukottai,Tamil Nadu, India.
5Dr.S.Arun, Professor, Department of ECE, Prathyusha Engineering College, Chennai, India.
Manuscript received on 15 September 2019 | Revised Manuscript received on 23 September 2019 | Manuscript Published on 11 October 2019 | PP: 1234-1238 | Volume-8 Issue-11S September 2019 | Retrieval Number: K124909811S19/2019©BEIESP | DOI: 10.35940/ijitee.K1249.09811S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Prediction of robot steps can be used in path exploring problems and application of data mining techniques, enhances navigational direction of robots. In this paper the proposed method is validated on the data sets using multi classification algorithms with four types of movement classes like Action-ahead, Sharp right turn, small in degree-right turn, and small in degree left turn in a separate layer. We obtain the results based on Meta classifiers’ accuracies tabulated. A layered approach is followed for obtaining the more accurate multi-classification.
Keywords: Data Mining, Classifiers, Multiclass, Layered approach, Multi-Classificat
Scope of the Article: Data Mining