Boosting Accuracy with Voting Classifiers In machine learning, combining multiple models often leads to better performance than relying on a single one. A Voting Classifier is a simple ensemble method that does just that — it aggregates predictions from several models to improve accuracy. There are two types: Hard Voting: Takes the majority vote from […]
Elastic Net Regressor
Elastic Net regression is a linear regression method that merges the strengths of both Lasso (L1) and Ridge (L2) regression techniques. It helps reduce overfitting and is especially effective when working with datasets that have many features, particularly when some of those features are highly correlated. The model’s regularization is controlled by two key hyperparameters: […]