Return 3D array instead of list of arrays for multioutput `.predict_proba()`

### Describe the workflow you want to enable

Currently, using `.predict_proba()` for multioutput predictions returns a list of `np.ndarray`, consisting of 2D arrays of shape `(n_samples, 2)`, with probabilities of class 0 and 1. This is quite surprising, since in all other cases pure `np.ndarray` is returned. This also makes reshaping the output inconvenient, requiring a call to `np.array()`.

For example, to get positive class probabilities, e.g. to compute multioutput AUROC, I have to do (typing for clarity):
```
preds: list[np.ndarray] = clf.predict_proba(X_test)
preds: np.ndarray = np.array(preds)
y_score = preds[:, :, 1].T
```

Only then the resulting `y_score` has shape `(n_samples, n_tasks)`, with predicted class 1 probability in columns.

### Describe your proposed solution

Return `np.ndarray` instead of list of arrays in the multioutput case. Just calling `np.array()` internally would be enough.

### Describe alternatives you've considered, if relevant

It could also be nice to include a utility function to extract positive class probabilities. `y_score = preds[:, :, 1].T` is quite non-obvious transformation, while also being necessary in practice to compute column-wise metrics based on probability.

### Additional context

_No response_


EDIT:

I also found another bug caused by the current implementation. In grid search CV, when using any multioutput prediction, this line will error: https://github.com/scikit-learn/scikit-learn/blob/545d99e0fd1de69b317496c77bd5c92a46cd1a9e/sklearn/utils/_response.py#L52. Error:
```
Traceback (most recent call last):
  File "/home/jakub/.cache/pypoetry/virtualenvs/scikit-fingerprints-VjWItXgH-py3.9/lib/python3.9/site-packages/sklearn/model_selection/_validation.py", line 971, in _score
    scores = scorer(estimator, X_test, y_test, **score_params)
  File "/home/jakub/.cache/pypoetry/virtualenvs/scikit-fingerprints-VjWItXgH-py3.9/lib/python3.9/site-packages/sklearn/metrics/_scorer.py", line 279, in __call__
    return self._score(partial(_cached_call, None), estimator, X, y_true, **_kwargs)
  File "/home/jakub/.cache/pypoetry/virtualenvs/scikit-fingerprints-VjWItXgH-py3.9/lib/python3.9/site-packages/sklearn/metrics/_scorer.py", line 371, in _score
    y_pred = method_caller(
  File "/home/jakub/.cache/pypoetry/virtualenvs/scikit-fingerprints-VjWItXgH-py3.9/lib/python3.9/site-packages/sklearn/metrics/_scorer.py", line 89, in _cached_call
    result, _ = _get_response_values(
  File "/home/jakub/.cache/pypoetry/virtualenvs/scikit-fingerprints-VjWItXgH-py3.9/lib/python3.9/site-packages/sklearn/utils/_response.py", line 214, in _get_response_values
    y_pred = _process_predict_proba(
  File "/home/jakub/.cache/pypoetry/virtualenvs/scikit-fingerprints-VjWItXgH-py3.9/lib/python3.9/site-packages/sklearn/utils/_response.py", line 49, in _process_predict_proba
    if target_type == "binary" and y_pred.shape[1] < 2:
AttributeError: 'list' object has no attribute 'shape'
```

So this is not only a feature request, but also a bugfix.

COMMENT:
@Rachit23110261 Please do not copy-paste generic answer from ChatGPT. It does not bring any values.

Labels: New Feature