Utility

Utility refers to the measure of the usefulness of a machine learning model in solving a specific problem. It is a measure of how well a model can predict the outcome of a given input. The utility of a model is determined by its accuracy, precision, recall, and F1 score. Accuracy measures the percentage of correct predictions made by the model, while precision measures the percentage of true positive predictions out of all positive predictions. Recall measures the percentage of true positive predictions out of all actual positive cases, and F1 score is the harmonic mean of precision and recall. A model with high utility is considered to be effective in solving the problem it was designed for.
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