Prediction of Cardiovascular Disease Using PySpark Techniques

Abstract

Abstract: On a day after day, human life is affected by differing kinds of diseases that is why their life is in distress. cardiovascular disease may be a generic class of disease that's effective in spreading infections and notably, it affects the heart and veins. it's determined that vessel diseases have become modest in old individuals besides in children too. it's terribly requisite to portend this sort of illness within the starting phases; many varieties of tests square measure used for diagnosticating these ailments. This implementation has been done by employing a big data tool that's Apache Spark and victimization spark's MLlib and PySpark libraries that square measure integrated with it. Apache Spark is among the foremost wide used big data technologies, and it's a stack of some libraries that are Spark SQL, Spark MLlib, Spark Streaming, etc. This analysis work aims to create a prediction model to predict whether or not people have cardiovascular disease or not, using machine learning classification techniques that embrace logistic regression, decision tree, random forest to enhance the performance of models. They compared the analysis of all applied machine learning models. The results obtained are compared with the results of existing models within the same domain and located to be improved. Keywords: heart, blood vessels, Xampp server, data analytics, cardiovascular diseases.