Analysis and Comparison of Prediction of Heart Disease Using Novel Genetic Algorithm and XGBoost Algorithm

Abstract

Aim: Prediction of coronary sickness utilizing novel genetic algorithm and contrasting its accuracy with XG boost algorithm. Materials and methods: Two models are proposed for foreseeing the accuracy (%) of coronary infection. To be unequivocal, a novel genetic algorithm and XG boost algorithm. Here we take 20 samples each for evaluation and analysis. Result: The novel genetic algorithm gives better accuracy (88.35%) than the XG boost accuracy (81.88%). Along these lines the genuine meaning of novel genetic algorithms is superior to XGBoost calculation with significance value of 0.115 Conclusion: From the outcome, it may very well be accumulated that a novel genetic algorithm helps in expecting the coronary affliction with more precision shown distinctively corresponding to XGBoost algorithm.