Ensemble Methods (Bagging, Boosting, Rando | |
Ensemble methods are a powerful technique in machine learning that combine the strengths of multiple models to create a single, more robust and accurate predictor. Imagine a group of experts working together to solve a complex problem. Each expert brings their own perspective and knowledge to the table, and by combining their insights, they can arrive at a better solution. Ensemble methods work in a similar way, leveraging the collective intelligence of multiple models to improve overall performance. Here are three popular ensemble methods: | |
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