With a precision of 86% and model's CAP curve showing an accuracy of 100%! This means it is capable of correctly predicting 100% of patients with a heart disease after processing 50% of the data. The model's performance is "Too Good to be True"! However, with Train accuracy = 86% and Test accuracy = 82%, there is no visible sign of overfitting.

Content: Machine Learning, Logistic regression steps, Probability matrix, Confusion matrix, Accuracy score, Recall value, Data preprocessing, Label encoding, Scaling the data, Splitting train test data, Running Logistic Regression, Y prediction on test data, Class imbalance, Type 1 & Type 2 errors.