With reference to evaluation stage of AI project cycle, explain the term Accuracy. Also give the formula to calculate it.
Generated by claude-sonnet-4-6 · 2026-06-21 03:18 · grounding rag
Model Answer
Accuracy is an evaluation metric that measures the total number of predictions a model gets right. The accuracy of the model and its performance are directly proportional — the better the performance, the more accurate the predictions.
Formula:
$$\text{Accuracy} = 1 - \text{Error Rate}$$
where $\text{Error Rate} = \dfrac{\text{Error (Actual - Predicted)}}{\text{Actual Value}}$
Accuracy% = Accuracy × 100%
Source: Chapter 3, Section 3.3 — Accuracy and Error
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Explanation
- The examiner expects two things: a definition of accuracy AND the formula — both are needed for full 2 marks.
- The formula is presented in the textbook's activity table, so use the step-by-step form: Error → Error Rate → Accuracy = 1 − Error Rate.
- Do not confuse this regression-style accuracy formula with classification accuracy (correct predictions / total predictions) — stick to what the source passage shows.