Paper Title : Diabetes Disease Prediction Using Machine Learning And Deep Learning Techniques
ISSN : 2394-2231
Year of Publication : 2021
MLA Style: K.E.Eswari MCA., M.Phil., M.E, S.Vijaya rohini "Diabetes Disease Prediction Using Machine Learning And Deep Learning Techniques " Volume 8 - Issue 2 March-April , 2021 International Journal of Computer Techniques (IJCT) ,ISSN:2394-2231 , www.ijctjournal.org
APA Style: K.E.Eswari MCA., M.Phil., M.E, S.Vijaya rohini "Diabetes Disease Prediction Using Machine Learning And Deep Learning Techniques " Volume 8 - Issue 2 March-April , 2021 International Journal of Computer Techniques (IJCT) ,ISSN:2394-2231 , www.ijctjournal.org
The diabetes is a disease caused due to the increase level of blood glucose. With the growth of Machine Learning methods, we have got the flexibility to search out an answer to the current issue, we have got advanced system mistreatment information processing that has the power to forecast whether the patient has polygenic illness or not. Data science methods have the potential to benefit other scientific fields by shedding new light on common questions. One such task is to assist make predictions on medical data. Machine learning is an emerging scientific field in data science handling the ways during which machines learn from experience. The aim of this project is to develop a system which may perform early prediction of diabetes for a patient with a better accuracy by combining the results of different machine learning techniques The main motivation of doing this project is to present a diabetes prediction model for the prediction of occurrence of diabetes. The aim of this analysis is to develop a system which could predict the diabetic risk level of a patient with a far better accuracy. Model development is based on categorization methods as Decision Tree, Naive Bayes, SVM algorithms and ANN. The main objective of this significant research work is to spot the simplest classification algorithm suitable for providing maximum accuracy when classification of normal and abnormal person is administered .
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— Machine Learning , Deep Learning, Support vector machine, Artificial Neural Network, Decision Tree, Naive Bayes, Data Mining.