Artificial Intelligence and Machine Learning
AI and ML
F1 score is the weighted average (harmonic mean) of precision and recall. The F1 score is calculated by the following formula: F1 score = (2 x Precision x Recall)/(Precision + Recall) The more the precision and recall metrics deviate from each other, the worse their harmonic mean (i.e. the F1 score).
Fitting or training in machine learning is the process by which a model learns from input data. Fitting is another word for training an ML model. Besides the ideal best fit or good fit, a model can get overfitted when overfitting occurs or it can get underfitted when underfitting occurs.