1.

What is F1 score? How would you use it?

Answer»

Let’s have a look at this table before directly jumping into the F1 SCORE.

PredictionPredicted YesPredicted No
Actual YesTrue Positive (TP)False Negative (FN)
Actual NoFalse Positive (FP)True Negative (TN)

In binary classification we consider the F1 score to be a measure of the MODEL’s accuracy. The F1 score is a WEIGHTED average of precision and recall SCORES.

F1 = 2TP/2TP + FP + FN

We see scores for F1 between 0 and 1, where 0 is the worst score and 1 is the best score. 
The F1 score is typically used in information retrieval to see how WELL a model retrieves relevant results and our model is performing.
 


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