What is the F1 score in scikit-learn?

What is the F1 score in scikit-learn?

The F1 score is a measure of a model's accuracy that considers both precision and recall. It's particularly useful for imbalanced datasets.

How do I calculate the F1 score using scikit-learn?

You can calculate the F1 score using the f1_score function from the sklearn.metrics module. Just pass your true labels and predicted labels as arguments.

Can you show me an example of calculating the F1 score?

Sure! Here's a simple example:

from sklearn.metrics import f1_score

# True labels
y_true = [0, 1, 1, 0, 1]
# Predicted labels
y_pred = [0, 1, 0, 0, 1]

# Calculate F1 score
f1 = f1_score(y_true, y_pred)
print(f1)

What does a high F1 score indicate?

A high F1 score indicates a good balance between precision and recall, meaning your model is performing well in classifying the positive class.