F1 Score Explained Simply | Classification Metrics

F1 Score is a classification metric that combines Precision and Recall into one balanced score. In this video, we explain F1 Score in a simple way: what F1 Score means why it combines Precision and Recall why it is useful for imbalanced data why high Precision alone is not enough why high Recall alone is not enough when F1 Score should be used Precision helps us understand false alarms. Recall helps us understand missed cases. F1 Score helps us balance both. In the next video, we’ll continue with Logistic Regression. Like this video, follow for more, and subscribe so you don’t miss the rest of the Machine Learning series. #MachineLearning #F1Score #Precision #Recall #Classification #DataScience #MLBasics #ArtificialIntelligence #TechWithAdyn