Prediction of heart disease risk using machine learning

Heart disease problems are the major threats to the human population. The term cardiovascular problems are related to many and various diseases causing harm to human heart. Today the leading source of human lives loss around the globe is cardiovascular disease problem that is resulting to harmful. In medical profession the difficult part is to predict when the heart attack will come since it required more experience and deep knowledge. Although, heart rate monitoring play’s important role on the measurement of the prestige factor that causes heart attack. Through this paper, I made a effort to explain the layout for heart rate problems along with the well know and trending technique that is data mining and how to use a machine learning technique is also explained that are mentioned as PCA (Principal Component Analysis) and SVM (Support Vector Machine) classification algorithm to discuss the prediction about the heart attack disease by using the heart analyzed data and various other health concern related perimeter collected from patients. In this project we have used Data Mining concepts. The process that is popular in today’s time i.e. Data mining, to make an analyses and study the number of item present data sets and then extracts the significant and relevant data. It helps to predict the patterns and paradigms, allowing business in decision making. The foremost ways for changing the raw data into predict full information can be possible by data mining for decision and training purpose.