set_output doesn't work for inverse_transform method

### Describe the bug

Using `set_output(transfrom="pandas")` doesn't return a pandas dataframe for the StandardScaler's `inverse_transform` method.

### Steps/Code to Reproduce

```python
from sklearn.preprocessing import StandardScaler
from sklearn.datasets import load_breast_cancer

X, _ = load_breast_cancer(return_X_y=True, as_frame=True)

scaler = StandardScaler().fit(X)
Xt = scaler.transform(X)

print(scaler.inverse_transform(Xt))
```

### Expected Results

I expect a pd.DataFrame in return, just like with the `transform` method.

### Actual Results

A numpy array.

```
[[1.799e+01 1.038e+01 1.228e+02 ... 2.654e-01 4.601e-01 1.189e-01]
 [2.057e+01 1.777e+01 1.329e+02 ... 1.860e-01 2.750e-01 8.902e-02]
 [1.969e+01 2.125e+01 1.300e+02 ... 2.430e-01 3.613e-01 8.758e-02]
 ...
 [1.660e+01 2.808e+01 1.083e+02 ... 1.418e-01 2.218e-01 7.820e-02]
 [2.060e+01 2.933e+01 1.401e+02 ... 2.650e-01 4.087e-01 1.240e-01]
 [7.760e+00 2.454e+01 4.792e+01 ... 0.000e+00 2.871e-01 7.039e-02]]
```

### Versions

```shell
System:
    python: 3.11.2 (tags/v3.11.2:878ead1, Feb  7 2023, 16:38:35) [MSC v.1934 64 bit (AMD64)]
executable: C:\Users\Mavs\Documents\Python\ATOM\venv311\Scripts\python.exe
   machine: Windows-10-10.0.19045-SP0
Python dependencies:
      sklearn: 1.3.2
          pip: 23.3.1
   setuptools: 68.2.2
        numpy: 1.24.4
        scipy: 1.11.3
       Cython: 3.0.5
       pandas: 2.1.2
   matplotlib: 3.8.0
       joblib: 1.3.2
threadpoolctl: 3.2.0
Built with OpenMP: True
threadpoolctl info:
       user_api: blas
   internal_api: openblas
    num_threads: 16
         prefix: libopenblas
       filepath: C:\Users\Mavs\Documents\Python\ATOM\venv311\Lib\site-packages\numpy\.libs\libopenblas64__v0.3.21-gcc_10_3_0.dll
        version: 0.3.21
threading_layer: pthreads
   architecture: Zen
       user_api: openmp
   internal_api: openmp
    num_threads: 16
         prefix: vcomp
       filepath: C:\Users\Mavs\Documents\Python\ATOM\venv311\Lib\site-packages\sklearn\.libs\vcomp140.dll
        version: None
       user_api: blas
   internal_api: openblas
    num_threads: 16
         prefix: libopenblas
       filepath: C:\Users\Mavs\Documents\Python\ATOM\venv311\Lib\site-packages\scipy.libs\libopenblas_v0.3.20-571-g3dec11c6-gcc_10_3_0-c2315440d6b6cef5037bad648efc8c59.dll
        version: 0.3.21.dev
threading_layer: pthreads
   architecture: Zen
       user_api: openmp
   internal_api: openmp
    num_threads: 8
         prefix: libiomp
       filepath: C:\Users\Mavs\Documents\Python\ATOM\venv311\Lib\site-packages\torch\lib\libiomp5md.dll
        version: None
       user_api: openmp
   internal_api: openmp
    num_threads: 1
         prefix: libiomp
       filepath: C:\Users\Mavs\Documents\Python\ATOM\venv311\Lib\site-packages\torch\lib\libiompstubs5md.dll
        version: None
```

COMMENT:
@sky-2002 I took a look into this and my best guess is that you could add a `as_frame` parameter to `sklearn.preprocessing.StandardScaler.inverse_transform()` and return `X` as a dataframe if `as_frame` is `True`. To my understanding that can be done by adding to the code found [here](https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/preprocessing/_data.py). Again, I only took a very quick glance at this so correct me if I'm mistaken @glemaitre.

UPDATE: Linked [here](https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/datasets/_base.py) is an implementation of `as_frame` for `sklearn.datasets.load_breast_cancer`.

Labels: New Feature