• Sahil Sharma
• Dr. Renu Puri

Data mining is a procedure that helps to extract important information from erratic data. The present data is used to forecast the future outcomes in the prediction analysis. This research aimed at forecasting heart disorders. This method is applied in stages to predict the occurrence of heart disease, during which data pre-processing, attribute extraction, and classification are carried out. The execution of both RF and LR algorithms is part of a hybrid method. To abstract the features, the RF algorithm is used. LR is used to categorize the photos. This study makes use of a number of indicators to evaluate the effectiveness of the suggested strategy. The newly developed method predicts heart disease with 95% accuracy.

Heart Disorder, Machine Learning, Feature Extraction, Hybrid Classification , Heart Disease Predication.

"Hybrid Classification Technique for the Heart Disease Prediction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 11, page no.e410-e418, November-2022, Available :http://www.jetir.org/papers/JETIR2211469.pdf

"Hybrid Classification Technique for the Heart Disease Prediction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 11, page no. ppe410-e418, November-2022, Available at : http://www.jetir.org/papers/JETIR2211469.pdf