Evaluating the Performance of Classification Algorithms using Ebola Virus Dataset

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2018
Authors:
Kanika Chuchra, Richa Vasuja, Ayesha Bhandralia
10.5120/ijca2018916863

Kanika Chuchra, Richa Vasuja and Ayesha Bhandralia. Evaluating the Performance of Classification Algorithms using Ebola Virus Dataset. International Journal of Computer Applications 179(38):26-28, April 2018. BibTeX

@article{10.5120/ijca2018916863,
	author = {Kanika Chuchra and Richa Vasuja and Ayesha Bhandralia},
	title = {Evaluating the Performance of Classification Algorithms using Ebola Virus Dataset},
	journal = {International Journal of Computer Applications},
	issue_date = {April 2018},
	volume = {179},
	number = {38},
	month = {Apr},
	year = {2018},
	issn = {0975-8887},
	pages = {26-28},
	numpages = {3},
	url = {http://www.ijcaonline.org/archives/volume179/number38/29326-2018916863},
	doi = {10.5120/ijca2018916863},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Highly fatal Ebola virus disease has emerged in Africa and got declared as public health emergency by W.H.O. many humans got infected by the virus so mining of disease is done using WEKA tool to predict whether is died or not by analyzing various symptoms. Various classification algorithms have been used. Further to improve the accuracy rate fusion of algorithm is done using unsupervised filter in MATLAB.

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Keywords

Ebola virus, WEKA, big data, classification Algorithms, filter