INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
Researchers have shown a lot of interest towards the field of medical science. A significant number of researchers have uncovered various reasons for premature human death. According to the literature that pertains to the subject, various reasons are responsible for the development of diseases, and one such cause is conditions affecting the heart. Many researchers proposed idiosyncratic methods to preserve human life and help health care experts to recognize, prevent and manage heart disease. The expert's decision can be supported by certain convenient methods, but every effective plan also has its limitation. The proposed approach robustly analyse an act of Decision Tree, Random Forest, XGBoost and Hybrid Model. After analysing the procedure the intended method smartly builds. Initially, the intention is to select the most appropriate method and analysing the act of available schemes executed with different features for examining the statistics.
"Hybrid Machine learning Classification technique to predict the accuracy of heart disease", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 4, page no.1136 - 1138, April-2023, Available :http://www.ijsdr.org/papers/IJSDR2304186.pdf
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Publication Details:
Published Paper ID: IJSDR2304186
Registration ID:205270
Published In: Volume 8 Issue 4, April-2023
DOI (Digital Object Identifier):
Page No: 1136 - 1138
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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