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ENSEMBLE MODELING
When making important decisions, we generally prefer to collate multiple opinions as opposed to listening to a single perspective or the first person to voice their opinion. Similarly, it’s important to consider and trial more than one algorithm to find the best model for your data. In advanced machine learning, it can even be advantageous to combine algorithms or models using a method called ensemble modeling, which amalgamates outputs to build a unified prediction model. By combining the output of different models (instead of relying on a single estimate), ensemble modeling helps to build a consensus on the meaning of the data. Aggregated estimates are also generally more accurate than any one technique. It’s ...
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