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- W4367331014 abstract "Aim: Comparison of accuracy rate in prediction of cardiovascular disease using Naive Bayes with Logistic Regression. Materials and Methods: The Naive Bayes (N=10) and Logistic Regression Algorithm (N=10) these two algorithms are calculated by using 2 Groups and taken 20 samples for both algorithm and accuracy in this work. 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 Naive Bayes (87.02%) over the Logistic Regression algorithm (92.18%). Statistical significance difference between novel Naive Bayes 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 Naive Bayes." @default.
- W4367331014 created "2023-04-30" @default.
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- W4367331014 date "2023-02-14" @default.
- W4367331014 modified "2023-09-24" @default.
- W4367331014 title "Estimation of Accuracy Rate in Predicting Cardiovascular Disease using Gaussian Naive Bayes Algorithm with Logistic Regression" @default.
- W4367331014 doi "https://doi.org/10.18137/cardiometry.2022.25.15321537" @default.
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