Page 303 - Ai Book - 10

u F1 Score: F1 score can be defined as the harmonic mean of the Precision and Recall. Thus, the formula is:
Precision * Recall
F1 Score = 2 *
Precision + Recall

The best value or the perfect value for an F1 score is 1 and the worst value is zero. You should remember
the following points about precision, recall and F1 score:
• If Precision is low and Recall is low, then F1 score is low.
• If Precision is low and Recall is high, then F1 score is low.

• If Precision is high and Recall is low, then F1 score is low.
• If Precision is high and Recall is high, then F1 score is high.
Now, calculate the accuracy,precision, recall and F1 score for the following scenario:
Scenario 1: In schools, a lot of times it happens that there is no water to drink. At a few places, cases of water
shortage in schools are very common and prominent. Hence, an AI model is designed to predict if there is going
to be a water shortage in the school in the near future or not. The confusion matrix for the same is:

The Confusion Matrix Reality: 1 Reality: 0

Predicted: 1 22 12

Predicted: 0 47 18

Calculate Accuracy, Precision, Recall and F1 Score for the above problem.

TP FP

22 12

47 18

(TP + TN)
Accuracy = × 100
(TP + TN + FP + FN)

22 + 18
= × 100
(22 + 18 + 12 + 47)

40
= × 100 = 40.04%
99

TP
Recall = = .31
TP + FN

TP
Precision = × 100
TP + FP

22
= × 100 = 64.70%
22 + 12
Precision × Recall
F1 Score =
Precision + Recall

177
177