Accuracy
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Accuracy
Accuracy in machine learning refers to the measurement of how often a classifier model correctly predicts a label for a given data point. It is calculated by dividing the number of correct predictions by the total number of predictions made. In general, accuracy is a useful metric for evaluating the performance of a model, but it may not always be the most appropriate metric depending on the specific problem being addressed.
