Quantum Machine Learning
Precision refers to the measure of how many true positive results are obtained from all positive predictions made by a model. It is an important metric in evaluating the performance of classification models, as it assesses the accuracy of positive predictions. High precision indicates that most of the predicted positive cases are indeed true positives, while low precision suggests that many of the predicted positives are false positives.
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