## models.deviance_score()


A score for [cross_validate](models.cross_validate.md#prospicio.models.cross_validate): the family's mean deviance on the


Usage

``` python
models.deviance_score(
    family,
    theta=None,
    power=None,
)
```


test rows, `sum(w * d) / sum(w)` with the test design's weights.


## Parameters


`family: str`  
As [Glm](models.Glm.md#prospicio.models.Glm).

`theta: float = None`  

`power: float = None`  


## Returns


`callable`  
`score(y_test, predicted, test_design) -> float`.


## Examples

``` python
>>> from prospicio.models import Design, deviance_score
>>> d = Design([[1.0, 1.0]], ["(Intercept)"])
>>> deviance_score("gaussian")([1.0, 3.0], [2.0, 2.0], d)
```

1.0