DEVELOPMENT OF MACHINE LEARNING MODEL FOR PREDICTION OF DIABETIC IN PATIENTS

The health care industry has become a major source of big data because of the digitization revolution. The examination of these data could be a fantastic resource for gaining fresh perspectives and raising people's awareness of health issues. Worldwide, diabetes and its complications are acknowledged as the biggest danger to public health. Diabetes is currently one of the most prevalent, chronic, and deadly diseases in the world due to various complications. In present work, healthcare data of female diabetic patient has been studied and derive the various insights from it. Machine learning algorithm such as logistic regression, decision tree, random forest classifier, Support Vector Machine (SVM) and K-Nearest Neighbour (KNN) classification has been used for prediction and modelling of the data. Python programming has been used as a tool for data analysis and various exploratory data analysis has been performed to determine the structure of the data. The predicted model found good relation with the collected data and gives a higher accuracy. This model help medical person to predict the risk associated for prediction of diabetic in female patients