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Bagging and Pasting in Machine Learning: Enhancing Model Performance through Ensemble Methods

In the previous blog on Ensemble Learning Explained, we explored the world of ensemble learning and how combining multiple models can often outperform even the most finely tuned single model. We looked at voting classifiers—arguably the most intuitive form of ensemble learning—where each model casts a vote and the majority wins. While voting is simple and surprisingly effective, it only scratches…

Bagging and Pasting in Machine Learning: Enhancing Model Performance through Ensemble Methods