# Setting up the model schema

We use the `Schema` class together with the `from_df` method to set up a schema from the reference data.

In this case, we define the problem as <mark style="color:purple;">'BINARY\_CLASSIFICATION'</mark> but other options like <mark style="color:purple;">'MULTICLASS\_CLASSIFICATION'</mark> and <mark style="color:purple;">'REGRESSION'</mark> are possible.

More info about the `Schema` class can be found in its [API reference](https://nannyml.github.io/nannyml-cloud-sdk/api_reference/monitoring/schema/).

```python
# Inspect schema from dataset and apply overrides
schema = nml_sdk.monitoring.Schema.from_df(
    'BINARY_CLASSIFICATION',
    reference_data,
    target_column_name='work_home_actual',
    ignore_column_names=('period'),
    identifier_column_name='id'
)
```