Implemented various classification models (Decision Tree, SVM, Neural Networks and Naïve Bayes) on PIMA diabetes dataset from Kaggle to predict whether a patient might likely suffer from diabetes in future or not.
The objective of the project is to analyze the PIMA INDIAN DIABETES DATABASE to predict the occurrence of diabetes.
•To prepare and train a model based on Naive bayes classifier and Neural Network.
•To prepare and train a model using SVM classifier to determine the effects of certain groups of driver variables on the potential target variable(outcome).Then determine which attributes are most impactful in decision making and analysis.
•To compare all the three models to determine which model has the best accuracy results.
- DATA SOURCE: Data for the project is taken from Kaggle.com, but this dataset is originally from National Institute of Diabetes and Digestive and Kidney disease.