diabetes_predction_scikit

It is a simple implementation of scikit-learn library. To run this exapmle, make sure to install panda, nupy and scikit in python. Main.py is the main file. indians-diabetes.data contains different data collected. test data is fed to program and prediction is made. The main aim of this project is the classification that can be performed to determine if a person is diabetic. The solution for this problem will also include the cost of the different types of data-sets. so that a doctor can safely and cost effectively select the best data-sets for the diagnosis of the disease. The major motivation for this work is that diabetes affects a large number of the world population and it’s a hard disease to diagnose. This is our main concern, to optimize the task of correctly selecting the set of medical tests that a patient must perform to have the best, the less expensive and time consuming diagnosis possible. A solution like this one, will not only assist doctors in making decisions, and make all this process more agile, it will also reduce health care costs and waiting times for the patients.