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).
Firmware Firmware is low level system software, which provides access and control to a computing device hardware and hardware abstraction layers to the computing device operating system. Depending on the complexity of a computing device, there may be devices with lower complexity, such as IoT devices and sensors, which do not need a full operating ... Read more
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.