Forecasting of Long term Renal disease using Machine learning

Long term renal Ailment[LRA] is sometimes referred as Long-term Renal Ailment is a prolonging Ailment that is accountable for affecting more than 10% of the world population. On an average it is responsible for affecting nearly 800 million people globally every year. Early detection and diagnosis play a crucial role in reducing the complications of the Ailment. Various machine learning algorithms such as Random Forest, Support Vector Machine, Decision Tree and Extreme Gradient Boosting with Multi class categorization have been used and the best algorithm is then used to develop the model which is capable of predicting the long term renal Ailment using image pro0cessing. For feature selection, cross-validation recursive feature removal and analysis of variance have been used.