Baselines
Learn how to use baselines to help you better assess your models.
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In ML, baselines serve as reference models that provide a benchmark for evaluating the performance of more complex models. Baseline models are typically simple and make minimal assumptions about the data.
They provide a starting point for model development and evaluation. They are relatively simple models that establish a minimum level of performance against which other models can be compared. Baselines are useful for assessing whether a more complex model provides significant improvements over a simple reference point.
Baseline models serve several purposes, including the following:
Performance evaluation: They provide a baseline against which the performance of more complex models can be compared.
Model complexity assessment: ...