f1-score

Vocabulary Word

Definition

'F1-score' is a special number that tells us how well a computer model is doing in its predictions. It's like our machine learning model's report card, checking if it is correctly predicting both 'yes' and 'no' cases.

Examples in Different Contexts

In machine learning, the 'F1 score' is a measure of a test's accuracy, considering both precision and recall to balance the trade-off between them. A data scientist might say, 'Optimizing the F1 score of our model ensures a balanced performance between detecting positives and avoiding false alarms.'

Practice Scenarios

Tech

Scenario:

The spam filter's precision has improved but we must confirm it isn't marking important mails as spam.

Response:

Looks good. But given that we deal with a lot of official communication, let's aim for a higher F1-score to avoid false positives.

Business

Scenario:

Our customer retention model's performance has been satisfactory, but we want to ensure it isn't missing appreciable opportunities.

Response:

We should tune the model for a better balance between precision and recall to improve the F1-score.