A baseline is a reference model, score, process, or result used to judge whether a more complex system provides improvement. In machine learning, a baseline helps define the minimum expected performance that a new model should exceed to justify additional complexity or cost.
A model used as a reference point for comparing how well another model (typically, a more complex one) is performing. For example, a logistic regression model might serve as a good baseline for a deep model. For a particular problem, the baseline helps model developers quantify the minimal expected performance that a new model must achieve for the new model to be useful.
A model used as a reference point for comparing how well another model (typically, a more complex one) is performing. For example, a logistic regression model might serve as a good baseline for a deep model. For a particular problem, the baseline helps model developers quantify the minimal expected performance that a new model must achieve for the new model to be useful. For more information, see Baseline and target datasets.