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How To Test Ai - How are AI models tested?


The purpose of testing an AI model is to assess the model's performance using either test data or fresh data sets. The accuracy recall, F-score, and confusion matrix (True and False positives, True and False negatives) are some of the metrics used to evaluate the performance. The findings are subsequently evaluated in relation to the accuracy criteria that were used to construct the model.