Abstract
The comparative study is performed on improved Novel Enhanced Gradient Boosting Algorithm (NEGB) and KNearest Neighbors (KNN) Algorithm, which determines the patient’s duration of staying in hospitals. The Novel Enhanced Gradient Boosting by taking the highest priority of maximized gain is proposed. The proposed algorithm implements Novel Enhanced Gradient Boosting framework with maximized gain probability. The Novel Enhanced Gradient Boosting algorithm and K-Nearest Neighbors Algorithm used in this research article. The concrete evidence for the performance evaluation, the sample size prejudge mental tools were used under the conditions of gpower 0.8, alpha 0.05 and confidence interval 95% during the estimation. The NEGB has a better accuracy rate (89.90%) compared to KNN has the accuracy rate (74.25%). The significance of 0.241 (p>0.05) value implies that experiment driven in this research was insignificant. The NEGB Algorithm is good in recalculating the stay duration of patients and also improves accuracy more than the K-Nearest Neighbors algorithm.