Life Expectancy: Prediction & Analysis using ML

Life expectancy (LE) models have vast effects on the social and financial structures of many countries around the world. Many studies have suggested the essential implications of Life expectancy predictions on social aspects and healthcare system management around the globe. These models provide many ways to improve healthcare and advanced care planning mechanism related to society. However, with time, it was observed that many present determinants were not enough to predict the longevity of the generic set of population. Previous models were based upon mortality-based knowledge of the targeted sampling population. With the advancement in forecasting technologies and rigorous work of the past, individuals have proposed this fact that other than mortality rate, there are still many factors needed to be addressed in order to deduce the standard Predicted Life Expectancy Models (PrLE). Due to this, now Life expectancy is being studied with some additional set of interests into educational, health, economic, and social welfare services. In the Analysis, the authors have implemented different machine learning algorithms and have achieved better accuracy based on pertinent features of the dataset.