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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Diabetes Prediction Usning Machine Learning |
| Authors Name: | P.Manoj Kumar , V. Sri Rama Raju , G. Sai Dharma , D. Pavan Kalyan |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_184927
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| Published Paper Id: | IJNRD2212164 |
| Published In: | Volume 7 Issue 12, December-2022 |
| DOI: | |
| Abstract: | Diabetes is an illness caused because of high glucose level in a human body. Diabetes should not be ignored if it is untreated then Diabetes may cause some major issues in a person like: heart related problems, kidney problem, blood pressure, eye damage and it can also affect other organs of human body. Diabetes can be controlled if it is predicted earlier. To achieve this goal this project work we will do early prediction of Diabetes in a human body or a patient for a higher accuracy through applying, Various Machine Learning Techniques. Machine learning techniques Provide better result for prediction by con- structing models from datasets collected from patients. In this work we will use Machine Learning Classification and ensemble techniques on a dataset to predict diabetes. Which are K-Nearest Neighbor (KNN), Logistic Regression (LR), Decision Tree (DT), Support Vector Machine (SVM), Gradient Boosting (GB) and Random Forest (RF). The accuracy is different for every model when compared to other models. The Project work gives the accurate or higher accuracy model shows that the model is capable of predicting diabetes effectively. Our Result shows that Random Forest achieved higher accuracy compared to other machine learning techniques. |
| Keywords: | Machine Learning, Logistic Regression, Decision Tree, SVM, Diabetes Prediction. |
| Cite Article: | "Diabetes Prediction Usning Machine Learning", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.7, Issue 12, page no.b555-b558, December-2022, Available :http://www.ijnrd.org/papers/IJNRD2212164.pdf |
| Downloads: | 000118759 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2212164 Registration ID: 184927 Published In: Volume 7 Issue 12, December-2022 DOI (Digital Object Identifier): Page No: b555-b558 Country: Vizianagaram, Andhra Pradesh, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2212164 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2212164 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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