Gradient Boosting Algorithm with Logistic Regression Estimation of Accuracy Rate in Predicting Cardiovascular Disease.

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Talluri Vishnuvardhan, A. Rama

Abstract

Aim: Estimation of accuracy rate in predicting the cardiovascular disease  using  gradient boosting algorithm with novel logistic regression. Materials and Methods: The prediction is done by Novel ANN (N=10) and  KNN (N=10) algorithms. The sample size is determined using the G power Calculator and it’s found to be 10. Results: Based on the results accuracy obtained in terms of accuracy is identified by Gradient boosting (91.00%) over the Logistic Regression algorithm (92.18%). The statistical significance difference between the novel gradient boosting algorithm and Logistic Regression Algorithm was found to be p=0.001 (2 tailed) (p<0.05). Conclusion: Prediction of cardiovascular disease using Logistic Regression is significantly better than the Gradient Boosting Algorithm.

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