A decision tree built in python for my 4th year module CA4010, Data Mining
The aim is to predict the accuracy based on certain attributes if a person does or does not have a heart disease. The dataset has been sourced from Kaggle [https://www.kaggle.com/datasets/bharath011/heart-disease-classification-dataset] The prediction model has an accuracy of 98.57% with an average time of 28s for the given dataset with 1200 rows
Kaggle: Dataset Source Microsoft Excel: Dataset R-Studio: Analyse the data’s central tendency Python: Language used to code the prediction model Decision Tree: Algorithm Implemented to calculate the classification
Top-down induction of decision trees Gini index Gini Impurity Decision tree