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Machine learning models are increasingly used in various applications to classify data into different categories. However, evaluating their performance is essential to ensure their accuracy and reliability. One of the key tools in this evaluation process is the confusion matrix. The confusion matrix, is a simple table that shows how well a classification model performs by comparing its predictions with real results. It categorizes predictions into four groups: correct predictions for both classe