IMPLEMENTATION METHODOLOGY
The proposed work is implemented in Python 3.6.4 with libraries scikit-learn, pandas, matplotlib and other mandatory libraries. We downloaded dataset from uci.edu. The data downloaded contains binary classes of heart disease. Machine learning algorithm is applied such as decision tree and random forest along with hybrid model.
DATA DICTIONARY
The dataset collected with attributes age, sex, cp, trestbps, chol, fbs, restecg, thalach, exang, oldpeak, slop, ca, thal, pred_attribute.
Modules
The modules included in our implementation are as follows
- Decision Tree
- Random forest
- Hybrid RF & Linear model
Python – Demo