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Call for Papers:Vol.11 Issue.3

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Title: :  Prediction of Heart Disease Using SVM and NAIVE Bayes
PaperId: :  8464
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 4 Issue 3 2018
DUI:    16.0415/IJARIIE-8464
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Neha DesaiPREC Loni, Ahmednagar, Maharashtra, India
Shital ChitalkarPREC Loni, Ahmednagar, Maharashtra, India
Rohini KashidPREC Loni, Ahmednagar, Maharashtra, India

Abstract

Computer Engineering
Classification Techniques, decision Tree algorithmic program, SVM, cardiopathy kNN, Naïve Bayes, Neural Network, Risk level, etc.
Nowadays, health disease is increasing day by day due to life style, hereditary. Especially, heart disease has become more common these days .i.e. life of people is at risk. Each individual has different values for Blood pressure, cholesterol and pulse rate. But according to medically proven results the normal values of Blood pressure is 120/90, cholesterol is and pulse rate is 72. This paper gives the survey about different classification techniques used for predicting the risk level of each person based on age, gender, Blood pressure, cholesterol, pulse rate. The patient risk level is classified using data mining classification techniques such as SVM, Naïve Bayes, kNN, and Decision Tree Algorithm, etc., Accuracy of the risk level is high when using more number of attributes.

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IJARIIE Neha Desai, Shital Chitalkar, and Rohini Kashid. "Prediction of Heart Disease Using SVM and NAIVE Bayes" International Journal Of Advance Research And Innovative Ideas In Education Volume 4 Issue 3 2018 Page 793-797
MLA Neha Desai, Shital Chitalkar, and Rohini Kashid. "Prediction of Heart Disease Using SVM and NAIVE Bayes." International Journal Of Advance Research And Innovative Ideas In Education 4.3(2018) : 793-797.
APA Neha Desai, Shital Chitalkar, & Rohini Kashid. (2018). Prediction of Heart Disease Using SVM and NAIVE Bayes. International Journal Of Advance Research And Innovative Ideas In Education, 4(3), 793-797.
Chicago Neha Desai, Shital Chitalkar, and Rohini Kashid. "Prediction of Heart Disease Using SVM and NAIVE Bayes." International Journal Of Advance Research And Innovative Ideas In Education 4, no. 3 (2018) : 793-797.
Oxford Neha Desai, Shital Chitalkar, and Rohini Kashid. 'Prediction of Heart Disease Using SVM and NAIVE Bayes', International Journal Of Advance Research And Innovative Ideas In Education, vol. 4, no. 3, 2018, p. 793-797. Available from IJARIIE, http://ijariie.com/AdminUploadPdf/Prediction_of_Heart_Disease_Using_SVM_and_Naïve_Bayes_ijariie8464.pdf (Accessed : ).
Harvard Neha Desai, Shital Chitalkar, and Rohini Kashid. (2018) 'Prediction of Heart Disease Using SVM and NAIVE Bayes', International Journal Of Advance Research And Innovative Ideas In Education, 4(3), pp. 793-797IJARIIE [Online]. Available at: http://ijariie.com/AdminUploadPdf/Prediction_of_Heart_Disease_Using_SVM_and_Naïve_Bayes_ijariie8464.pdf (Accessed : )
IEEE Neha Desai, Shital Chitalkar, and Rohini Kashid, "Prediction of Heart Disease Using SVM and NAIVE Bayes," International Journal Of Advance Research And Innovative Ideas In Education, vol. 4, no. 3, pp. 793-797, May-Jun 2018. [Online]. Available: http://ijariie.com/AdminUploadPdf/Prediction_of_Heart_Disease_Using_SVM_and_Naïve_Bayes_ijariie8464.pdf [Accessed : ].
Turabian Neha Desai, Shital Chitalkar, and Rohini Kashid. "Prediction of Heart Disease Using SVM and NAIVE Bayes." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 4 number 3 ().
Vancouver Neha Desai, Shital Chitalkar, and Rohini Kashid. Prediction of Heart Disease Using SVM and NAIVE Bayes. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2018 [Cited : ]; 4(3) : 793-797. Available from: http://ijariie.com/AdminUploadPdf/Prediction_of_Heart_Disease_Using_SVM_and_Naïve_Bayes_ijariie8464.pdf
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