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ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
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Issue: June 2022

Volume 7 | Issue 6

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Published Paper Details
Paper Title: Diabetes prediction using Random forest algorithm.
Authors Name: Ms.J.P. Srinithi , Mr.S.Ilangovan , Ms.A.Naishvini , Ms.T.P.Nivedita
Unique Id: IJSDR2205048
Published In: Volume 7 Issue 5, May-2022
Abstract: Diabetes is one of the most significant causes of mortality in the world today. Prediction of cardiovascular disease is a critical challenge in the area of clinical data analysis. Machine learning (ML) has been shown to be effective in assisting in making decisions and predictions from the large quantity of data produced by the healthcare industry. We have also seen ML techniques being used in recent developments in different areas of the Internet of Things (IoT). Various studies give only a glimpse into predicting heart disease with ML techniques.The prediction model is introduced with different combinations of features and several known classification techniques. The system is developed based on classification algorithms includes Random Forest, and Logistic Regression algorithms have been used. Machine learning is a huge field which learns from past experiences and gives proper predictions.
Keywords: Diabetes Prediction,Machine Learning,Missing values and outliers,Cloud data warehouse
Cite Article: "Diabetes prediction using Random forest algorithm.", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.7, Issue 5, page no.251 - 254, May-2022, Available :http://www.ijsdr.org/papers/IJSDR2205048.pdf
Downloads: 00096793
Publication Details: Published Paper ID: IJSDR2205048
Registration ID:200323
Published In: Volume 7 Issue 5, May-2022
DOI (Digital Object Identifier):
Page No: 251 - 254
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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