It is concerned with the analysis of the Coronary heart disease prediction with patient datasets including Machine Learning Algorithms. The prediction was made using various algorithms like Logistic Regression, Naive Bayes, Support Vector Machine (Linear), K-Nearest Neighbours, Decision Tree, Random Forest, and XGBoost. AMong then Random Forest Perform best.
The problem addressed here is classification, with input parameters such as sex, slope, ca, etc. and the target as a binary variable. Outcome: Based on the provided dataset it will predict coronary heart disease is present or not.