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What is ML Lab 7,8,9 about?

The document outlines a series of laboratory exercises focused on implementing and comparing various machine learning classification algorithms (SVM, Decision Tree, Random Forest, and XGBoost) on the Heart Disease dataset to determine the most accurate model for predicting heart disease. It includes objectives for data preprocessing, hyperparameter tuning, and model evaluation using accuracy and cross-validation metrics. Additionally, it covers K-Means clustering to identify optimal clusters and visualize d

Author

s83102797

Language

EN