northcampus-university-of-kashmir / heart-disease-detection-system

this repository is about to built a system that will detect whether person has heart disease or not using machine learning algorithms

last_edited2 contains actual implementation

we are using several classification Algorithm. 👇👇

1. Decision tree
2. Random Forest
3. K nearest neighbour
4. Logistic regression
5. support vector machine
5. xgboost
6. voting classifier

total accuracy we got with hyper-tuning is below in table

	Model	Testing Accuracy %	f1 test %	Precision test %	Recall test %
0	Random forest	82.42	84.00	84.00	84.00
1	KNN	86.81	88.00	88.00	88.00
2	Decision tree	78.02	78.72	84.09	74.00
3	Logistic Regression	86.81	88.24	86.54	90.00
4	SVM	87.91	88.89	89.80	88.00
5	Xgboost	83.52	84.85	85.71	84.00
6	Voting	83.52	84.85	85.71	84.00

heart-disease-detection-system's Issues

results csv was formed wrongly (svm and logistic reg) was showing same accuracy

Need to be fixed in final report file

Add feature importance

we need to add feature importance using decision tree in our report and ipynb file

load new dataset using pandas

do initial load using panadas