> ## Documentation Index
> Fetch the complete documentation index at: https://systematica.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Objectives

> systematica.tuners.optuna_.objectives

## `ObjectiveFullHistory`

```python theme={null}
ObjectiveFullHistory(
    validate_model: bool = True,
    debug: bool = True,
)
```

Objective for full history evaluation.

Method generated by attrs for class ObjectiveFullHistory.

### Ancestors

* `systematica.tuners.base.BaseOptunaObjective`
* `abc.ABC`

### Methods

#### `compute`

```python theme={null}
compute(
    self,
    model,
    search: dict,
    **feature,
) ‑> int | float | Tuple[int | float, ...]
```

Compute the objective value.

**Parameters**:

| Name     | Type     | Default | Description                                                                                       |
| -------- | -------- | ------- | ------------------------------------------------------------------------------------------------- |
| `model`  | `tp.Any` | `--`    | The model to be evaluated.                                                                        |
| `search` | `dict`   | `--`    | The hyperparameter search space. \*\*feature\_config Additional feature configuration parameters. |

**Returns**:

| Type                                          | Description                   |
| --------------------------------------------- | ----------------------------- |
| `int \| float \| tp.Tuple[int \| float, ...]` | The computed objective value. |

## `ObjectiveRollingWalkForward`

```python theme={null}
ObjectiveRollingWalkForward(
    validate_model: bool = True,
    debug: bool = True,
    reduce_func: Callable = _Nothing.NOTHING,
)
```

Objective for rolling walk-forward evaluation.

Method generated by attrs for class ObjectiveRollingWalkForward.

### Ancestors

* `systematica.tuners.base.BaseOptunaObjective`
* `abc.ABC`

### Instance variables

* `reduce_func: Callable`:

### Methods

#### `compute`

```python theme={null}
compute(
    self,
    model,
    search: dict,
    **feature,
) ‑> int | float | Tuple[int | float, ...]
```

Compute the objective value.

**Parameters**:

| Name     | Type     | Default | Description                                                                               |
| -------- | -------- | ------- | ----------------------------------------------------------------------------------------- |
| `model`  | `tp.Any` | `--`    | The model to be evaluated.                                                                |
| `search` | `dict`   | `--`    | The hyperparameter search space. \*\*feature Additional feature configuration parameters. |

**Returns**:

| Type                                          | Description                   |
| --------------------------------------------- | ----------------------------- |
| `int \| float \| tp.Tuple[int \| float, ...]` | The computed objective value. |