# What is Precision? Definition & Technical Mechanics

> **Source:** [SPIDITS AI AI Glossary](https://spidits.com/ai-glossary)  
> **Category:** Mathematical Foundations  
> **Canonical Citation:** [https://spidits.com/ai-glossary/precision](https://spidits.com/ai-glossary/precision)

## Definition
Precision (Positive Predictive Value) is a classification evaluation metric measuring the fraction of predicted positive examples that are actually correct, calculated as true positives divided by all predicted positives.

## Architectural Mechanics & Deep Dive
Precision is a performance metric that measures the proportion of correctly predicted positive instances out of all predicted positive instances (true positives divided by true positives plus false positives). It evaluates model quality, indicating how trustworthy the model is when it predicts a positive class, crucial for applications like spam filtering.

## Industry Applications & Real-World Use Cases
Model validation, spam classification audits, and search relevance metrics.

## Frequently Asked Questions

### What is the formula for classification precision?
`Precision = True Positives / (True Positives + False Positives)`.

### When should precision be prioritized over recall?
When the cost of a false positive is extremely high. For instance, in email spam filtering, a false positive means a legitimate email is blocked, making high precision critical.

## Related Terminology
- [recall](https://spidits.com/ai-glossary/recall)
- [accuracy](https://spidits.com/ai-glossary/accuracy)
- [f1-score](https://spidits.com/ai-glossary/f1-score)

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*From the SPIDITS AI Knowledge Base (336+ terms indexed). Explore full technical definitions: [https://spidits.com/ai-glossary](https://spidits.com/ai-glossary)*