In machine learning, model evaluation metrics are essential for assessing how well a model performs, especially in classification tasks. Among these metrics, the F1 Score stands out as a balanced measure that combines both precision and recall, making it invaluable when dealing with imbalanced datasets. This article explores the F1 Score, its relationship with metrics … Continue reading Understanding the F1 Score: A Harmonized Metric of Precision and Recall