Can I read Comparative Study of CVD Classification Algorithms on EtoBox?

Comparative Study of CVD Classification Algorithms by Dza Fadhlan is a document available to read on EtoBox.

What is Comparative Study of CVD Classification Algorithms about?

This study compares five machine learning algorithms—Support Vector Machine (SVM), K-Nearest Neighbor (K-NN), Logistic Regression (LR), Decision Tree (DT), and Naive Bayes (NB)—for classifying cardiovascular disease using a dataset from Kaggle. The research highlights the challenges posed by high-dimensional and imbalanced data in accurately diagnosing heart disease and concludes that SVM and LR are the most effective methods for this classification task. The paper emphasizes the importance of machine learn

Author

Dza Fadhlan

Language

EN