> ## 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.

# Recall

> Measures the completeness of positive predictions by calculating the proportion of true positives among all actual positives.

### Input

* **`output`** (str): The generated text (set of items)
* **`expectedOutput`** (str): The reference text (set of items)

### Output

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

## Interpretation

* **Higher scores (closer to 1)**: A larger fraction of actual positives are recovered (fewer false negatives)
* **Lower scores (closer to 0)**: Many actual positives were missed (more false negatives)

## Formula

$$
\mathrm{Recall} = \frac{\mathrm{TP}}{\mathrm{TP} + \mathrm{FN}}
$$

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

## Use Cases

* Medical diagnosis and anomaly detection
* Fraud detection
* Any task where missing positives is costly