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Multisample Classification in Clinical Decisions using Multi-Aggregative Factored K-NN Classifier

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Multisample Classification in Clinical Decisions using Multi-Aggregative Factored K-NN Classifier


P. Tamil Selvan | Dr. Senthil Kumar A.V

https://doi.org/10.31142/ijtsrd5774



P. Tamil Selvan | Dr. Senthil Kumar A.V "Multisample Classification in Clinical Decisions using Multi-Aggregative Factored K-NN Classifier" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-6, October 2017, pp.1037-1042, URL: https://www.ijtsrd.com/papers/ijtsrd5774.pdf

Classification in sample by sample process, a classifier is requested to combine information across multiple samples drawn from the same data source, the results are combined using a strategy such as majority are selected. To solve the problem of classification failure, a new hazard function in multisample classification is introduced ie Multi-aggregative factored K-NN Classifier. This method evaluates the classification of multisampling problems, such as electromyographic (EMG) data, by making aggregate features available to a per-sample classifier. It is found that the accuracy of this approach is superior to that of traditional methods such as majority selection for this problem. The classification improvements of this method, in conjunction with a confidence measure expressing the per-sample probability of classification failure (i.e., a hazard function) is described and measured. This paper compares the existing method Bayesian and the proposed Multi-aggregative factored KNN approach. The experimental results displayed a prominent improvement by using the proposed algorithm.

EMG, Motor Unit Action Potential, Additional Feature Sets, Classifier


IJTSRD5774
Volume-1 | Issue-6, October 2017
1037-1042
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

International Journal of Trend in Scientific Research and Development - IJTSRD having online ISSN 2456-6470. IJTSRD is a leading Open Access, Peer-Reviewed International Journal which provides rapid publication of your research articles and aims to promote the theory and practice along with knowledge sharing between researchers, developers, engineers, students, and practitioners working in and around the world in many areas like Sciences, Technology, Innovation, Engineering, Agriculture, Management and many more and it is recommended by all Universities, review articles and short communications in all subjects. IJTSRD running an International Journal who are proving quality publication of peer reviewed and refereed international journals from diverse fields that emphasizes new research, development and their applications. IJTSRD provides an online access to exchange your research work, technical notes & surveying results among professionals throughout the world in e-journals. IJTSRD is a fastest growing and dynamic professional organization. The aim of this organization is to provide access not only to world class research resources, but through its professionals aim to bring in a significant transformation in the real of open access journals and online publishing.

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