Project 1

Here are the accuracy results for each model in predicting heart disease:

Logistic Regression: 81.5%

K-Nearest Neighbors: 70%

Support Vector Machine: 55%

Decision Tree Classifier: 98%

Random Forest Classifier: 99.5%

Both the Decision Tree and Random Forest classifiers achieved the highest accuracy.

This suggests these models might be particularly effective for this dataset,

although further evaluation with additional metrics (e.g., precision, recall) could provide more insights

into their performance.