In this project model has been trained by Support Vector Machine to predict whether a new patient has diabetes based on certain features.
The dataset used in this project comes from the National Institute of Diabetes and Digestive and Kidney Diseases, and contains anonymized diagnostic measurements for a set of female patients.
Tasks included in this are
1: Loading a dataset from file, and extract its features and labels.
2: Spliting a dataset into training and testing subsets, and normalize the values.
3: Creating a support vector machine and train it.
4: Making a medical diagnosis for a new patient using an SVM.
5: Evaluating the accuracy of the SVM classifier.