> ## Documentation Index
> Fetch the complete documentation index at: https://www.getmaxim.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Precision

> Measures the accuracy of positive predictions by calculating the proportion of true positives among all predicted positives.

### Input

* **`output`** (str): The generated text (set of predicted positive items)
* **`expectedOutput`** (str): The reference text (set of ground-truth positive items)

### Output

* **`Result`** (float): A score between 0 and 1.

## Interpretation

* **Higher scores (closer to 1)**: A larger fraction of predicted positives are correct (fewer false positives)
* **Lower scores (closer to 0)**: Many predicted positives are incorrect (more false positives)

## Formula

$$
\mathrm{Precision} = \frac{\mathrm{TP}}{\mathrm{TP} + \mathrm{FP}}
$$

<Note>This is a **Similarity** Metric</Note>

## Use Cases

* Information retrieval and search relevance
* Classification tasks where avoiding false alarms is critical
* Evaluating the relevance of generated content