(simulate-multisite-data)=
# Multisite Data Simulation

## Overview

``uniharmony.datasets.make_multisite_classfication`` helps researchers generate synthetic datasets that mimic real-world multi-center studies.
Whether you're testing machine learning algorithms, developing statistical methods, or teaching data science concepts,
this simulator creates realistic data with built-in complexities that mirror actual research scenarios.

## Usage

```python
from uniharmony import make_multisite_classification

# Generate data with 3 sites, 500 samples total
X, y, sites = make_multisite_classification(
    n_sites=3,
    n_samples=500,
    n_features=20,
    random_state=42  # For reproducibility
)
# X contains your features
# y has labels
# sites tells you which site each sample came from
```

## Behind the Scenes

Each sample's features combine three components that can be adapted:

Feature = Signal + Noise + Site Effect

## Flexible Configuration

You can choose how many sites you want, set the total number of samples, control how many features and control the class balance.
Work with binary classification (yes/no) or multi-class problems.