News Updates Sunday 19th May 2024 :
  • Welcome to INPRESSCO, world's leading publishers, We have served more than 10000+ authors
  • Articles are invited in engineering, science, technology, management, industrial engg, biotechnology etc.
  • Paper submission is open. Submit online or at editor.ijcet@inpressco.com
  • Our journals are indexed in NAAS, University of Regensburg Germany, Google Scholar, Cross Ref etc.
  • DOI is given to all articles

Heart Disease prediction using machine learning


Author : Riddhi Kasabe and Prof.Dr. Geetika Narang

Pages : 1236-1238
Download PDF
Abstract

Data mining is the process of data analyzing from various perspectives and combining it into useful information. This technique is used for finding heart disease. Based on risk factor the heart diseases can be defined very easily. The main aim of this work is to evaluate different classification techniques in heart diagnosis. First, the heart numeric dataset is extracted and preprocess them. After that using extract the features that is condition to be find to be classified by machine learning. Compared to existing; machine learning provides better performance. After classification, performance criteria including accuracy, precision, F-measure is to be calculated. Machine learning provides better performance. The comparison measure expose that Random Forest is the best classifier for the diagnosis of heart disease on the existing dataset.

Keywords: Heart diagnosis, Data Mining,Machine Learning, Naive Bayes, Classification.

Call for Papers
  1. IJCET- May/June 2024 Issue

    Submission Last Date
    30 June 2024
  2. DOI is given to all articles
  3. Current Issue
  4. IJTT-June-2024
  5. IJAIE-June-2024
  6. IJCSB-June-2024
  • Inpressco Google Scholar
  • Inpressco Science Central
  • Inpressco Global impact factor
  • Inpressco aap

International Press corporation is licensed under a Creative Commons Attribution-Non Commercial NoDerivs 3.0 Unported License
©2010-2023 INPRESSCO® All Rights Reserved