SUPPORT VECTOR MACHINES: PREDICTING FUTURE - CASE STUDY

As previously promised in SUPPORT VECTOR MACHINE -- 3RD PART OF SUPERVISED LEARNING METHODS, let's talk about an amazing case study to analyze and comprehend the application of support vector into a real business problem and be ready for the amazing outcomes and prediction no one actually saw coming. In this problem statement, we'll study the case where we'll try to predict whether the person will survive based on the diagnostic factors influencing Hepatitis. Let's first talk about the dataset we are going to use. The dataset contains the occurrences of hepatitis in people. The UCI machine learning repository was used to get this data set.. It has 155 recordings in two separate types, 32 of which are death records and 123 of which are live records.