Accuracy
Accuracy is a statistical measure that determines how well a machine learning model can predict the outcome of new data. It is the ratio of the number of correct predictions to the total number of predictions made. In other words, accuracy measures the percentage of correct predictions made by the model. It is a commonly used metric to evaluate classification models. However, accuracy alone may not be sufficient to evaluate the performance of a model, especially when the data is imbalanced. In such cases, other metrics such as precision, recall, and F1 score should also be considered.
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