# `pp_vsn` — Variable Sorting Normalization

_Group_: **Signal transforms** · _Binding_: `n4m.sklearn.VariableSortingNormalization` · _C ABI_: `n4m_pp_vsn_*`

## Description

VSN-style data-derived weighted SNV.

### Parameters

| Name | Type | Default |
|------|------|---------|
| `eps` | `float` | `1e-12` |

## Explanations

### Bibliographic source

_Standard spectroscopic operator — see the nirs4all preprocessing / augmentation handbook and the cited literature within the binding docstring._

### Mathematical principle

VSN-style data-derived weighted SNV.

### Implementation

C ABI `n4m_pp_vsn_*` in libn4m (create / apply / destroy lifecycle), wrapped by `n4m.sklearn.VariableSortingNormalization`. The same numerical kernel backs every language binding.

### Usage

```python
from n4m.sklearn import VariableSortingNormalization
op = VariableSortingNormalization()
X_transformed = op.fit_transform(X)
```

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_See also_: [methods index](index.md) · [interactive dashboard](../landing/dashboard.md)