Heart Disease Prediction Based On Age Detection Using Novel Logistic Regression Over K-Nearest Neighbor

Heart Disease Prediction Based On Age Detection Using Novel Logistic Regression Over K-Nearest Neighbor

Aim: To improve the accuracy in Heart Disease Prediction using Novel Logistic Regression and K-NN Algorithm. Materials and Methods: This study contains 2 groups i.e Novel Logistic Regression and. Each group consists of a sample size of 10 and the study parameters include alpha value 0.01, beta value...

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Veröffentlicht in:CARDIOMETRY 2022-12 (25), p.1725-1730
Hauptverfasser: Karthi, C.B.M., Kalaivani, A.
Format: Artikel
Sprache:eng
Schlagworte:
Accuracy
Algorithms
Artificial intelligence
Cardiovascular disease
Datasets
Heart
Illnesses
Independent variables
Information technology
Liability
Literacy
Regression analysis
Sample size
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Zusammenfassung:Aim: To improve the accuracy in Heart Disease Prediction using Novel Logistic Regression and K-NN Algorithm. Materials and Methods: This study contains 2 groups i.e Novel Logistic Regression and. Each group consists of a sample size of 10 and the study parameters include alpha value 0.01, beta value 0.2, and the Gpower value of 0.8. Results: The Novel Logistic Regression (98.45) achieved improved accuracy than the K-NN Algorithm (79.82) in Heart Disease Prediction. The statistical significance difference is 0.01 (p
ISSN:2304-7232
DOI:10.18137/cardiometry.2022.25.17251730