Machine Learning

This study compares the performance of three models—Logistic Regression, Naïve Bayes, and Artificial Neural Network—on predicting heart attack risk. The Artificial Neural Network outperformed in accuracy, precision, recall, and F1-Score, making it the best model. Logistic Regression was strong in interpretability and simplicity.

Linear regression models relationships between variables by finding a best-fitting line. Using matrix inversion and the Ordinary Least Squares (OLS) method, it efficiently computes coefficients, simplifying the process and providing a clear mathematical framework. This guide covers fundamental concepts and practical applications of matrix algebra for solving linear regression.