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Evaluating the Performance of Classification Algorithms using Ebola Virus Dataset

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

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

	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 = {},
	doi = {10.5120/ijca2018916863},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


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