Confusion Matrix for an AI model that predicts whether there is a chance of earthquake or not.
Recently the country was shaken up by a series of earthquakes which has done a huge damage to the people as well as the infrastructure. To address this issue, an AI model has been created which can predict if there is a chance of earthquake or not. The confusion matrix for the same is given. Answer the following:
Generated by claude-sonnet-4-6 · 2026-06-21 03:18 · grounding stimulus
Model Answer
(i) True Negative (TN):
True Negative means the model predicted No earthquake, and in reality there was No earthquake.
From the table: TN = 20
(ii) Calculations:
From the confusion matrix:
- TP = 50, FP = 5, FN = 25, TN = 20
- Total = 100
$$\text{Precision} = \frac{TP}{TP + FP} = \frac{50}{50 + 5} = \frac{50}{55} \approx 0.909$$
$$\text{Recall} = \frac{TP}{TP + FN} = \frac{50}{50 + 25} = \frac{50}{75} \approx 0.667$$
$$\text{F1 Score} = \frac{2 \times \text{Precision} \times \text{Recall}}{\text{Precision} + \text{Recall}} = \frac{2 \times 0.909 \times 0.667}{0.909 + 0.667} \approx \frac{1.212}{1.576} \approx \mathbf{0.769}$$
Source: Confusion Matrix (AI), Class 10 IT/CS
---
Explanation
- TN is always the "Predicted No & Reality No" cell — easy 1 mark.
- For part (ii), correctly identify all four values (TP, FP, FN, TN) first — examiners award method marks for this.
- Show the formula, substitution, and final value for each metric to secure full marks.
- F1 Score is the harmonic mean of Precision and Recall — remember the formula exactly.