A Review of efficient heart disease classification approach using data mining techniques

Authors

  • Hetasvi R. Ribadiya M.E. Scholar, Computer Engineering, Darshan Institute of Engineering & Technology, Rajkot
  • Prof. Swati Sharma Assistant Professor, Computer Engineering, Darshan Institute of Engineering & Technology, Rajkot

Keywords:

accuracy, performance, KNN, Naïve Bayes, SHGB

Abstract

In this inquire about, we point to foresee exactness, whether the person is at chance of a heart illness. This
forecast will be done by applying machine learning calculations on preparing information that we offer. Once the individual
enters the data that is requested, the calculation is connected and the result is produced. Clearly, the exactness is anticipated
to diminish when the medical information itself are deficient. We execute the expectation show over real-life healing center
information. We have proposed assist by applying SHGB(STOCHASTIC HIGH GRADIENT BOOSTING) ALGORITHM data
mining or machine learning calculations over the preparing information to foresee the hazard of maladies, comparing their
accuracies so that ready to conclude the foremost exact one. Properties can too be adjusted in an endeavor to make strides
the precision assist in terms of accuracy.

Published

2021-02-25

How to Cite

Hetasvi R. Ribadiya, & Prof. Swati Sharma. (2021). A Review of efficient heart disease classification approach using data mining techniques. International Journal of Advance Engineering and Research Development (IJAERD), 8(2), 33–36. Retrieved from https://www.ijaerd.org/index.php/IJAERD/article/view/4647