F1 score
- Machine Learning course
- Beginner
- Lesson 69/112
- 5 min
F1 score is the harmonic mean of precision and recall.
The F1 score
F1 is the harmonic mean of precision and recall: 2·P·R / (P + R). If either is low, F1 is low too; an arithmetic mean would hide this.
P, R = 1.0, 0.1
print((P + R) / 2) # 0.55 misleading
print(2 * P * R / (P + R)) # 0.18 realisticIt is often used as a single summary metric in imbalanced problems where both false alarms and misses matter.
classification_report
classification_report gives the precision, recall, F1 and support (example count) for each class in a single table:
from sklearn.metrics import classification_report
print(classification_report(y_test, y_pred, digits=3))In the bottom rows, macro avg weights classes equally and weighted avg by class size.
Practice Four metrics
For the given labels, print accuracy, precision, recall and F1 with round(..., 3) in a single print, separated by spaces.
Starter code
from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score
y_true = [1, 1, 1, 1, 0, 0, 0, 0, 0, 0]
y_pred = [1, 1, 1, 0, 1, 0, 0, 0, 0, 0]
# buraya yazSample solution
from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score
y_true = [1, 1, 1, 1, 0, 0, 0, 0, 0, 0]
y_pred = [1, 1, 1, 0, 1, 0, 0, 0, 0, 0]
print(round(accuracy_score(y_true, y_pred), 3), round(precision_score(y_true, y_pred), 3), round(recall_score(y_true, y_pred), 3), round(f1_score(y_true, y_pred), 3))Expected output
0.8 0.75 0.75 0.75
Questions and answers
Review the lesson questions together with their answers. To test yourself, solve the lesson interactively.
1 If precision is 0.5 and recall is 0.5, what is F1?
- 1.0
- 0.75
- 0.5 Correct answer
- 0.25
Explanation: 2 · 0.5 · 0.5 / (0.5 + 0.5) = 0.5; if both are equal, F1 is the same.
2 Compute the F1 score.
f = ____(y_true, y_pred)f = f1_score(y_true, y_pred)Explanation: f1_score gives the harmonic mean of precision and recall.
3 Match the report rows.
| Term | Meaning |
|---|---|
precision |
Hit rate when saying positive |
recall |
Share of positives caught |
f1-score |
Harmonic mean |
support |
Examples in the class |