set_config(transform_output="pandas") causes error in Isomap

### Describe the bug

I am getting an error when using the awesome `set_config(transform_output="pandas")` in combination with Isomap. The Error says "AttributeError: 'DataFrame' object has no attribute 'dtype'", so my temporary solution is to switch back to the default config.

I am working with version 1.3.1 (latest I could find).

### Steps/Code to Reproduce

```python
import numpy as np
import pandas as pd
from sklearn.manifold import Isomap
from sklearn import set_config

# generate random data
n_rows = 500
n_cols = 30
X = pd.DataFrame(
    data=np.random.random((n_rows, n_cols)),
    columns=[f"x{i}" for i in range(n_cols)]
)

# this works
set_config(transform_output="default")
Isomap(n_neighbors=5, n_components=2, p=1).fit_transform(X)

# this fails
set_config(transform_output="pandas")
Isomap(n_neighbors=5, n_components=2, p=1).fit_transform(X)
```

### Expected Results

No error is thrown and transformed results are returned.

### Actual Results

```
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "...\Anaconda3\envs\...\lib\site-packages\sklearn\utils\_set_output.py", line 157, in wrapped
    data_to_wrap = f(self, X, *args, **kwargs)
  File "...\Anaconda3\envs\...\lib\site-packages\sklearn\base.py", line 1152, in wrapper
    return fit_method(estimator, *args, **kwargs)
  File "...\Anaconda3\envs\...\lib\site-packages\sklearn\manifold\_isomap.py", line 383, in fit_transform
    self._fit_transform(X)
  File "...\Anaconda3\envs\...\lib\site-packages\sklearn\manifold\_isomap.py", line 309, in _fit_transform
    self.embedding_ = self.kernel_pca_.fit_transform(G)
  File "...\Anaconda3\envs\...\lib\site-packages\sklearn\utils\_set_output.py", line 157, in wrapped
    data_to_wrap = f(self, X, *args, **kwargs)
  File "...\Anaconda3\envs\...\lib\site-packages\sklearn\decomposition\_kernel_pca.py", line 469, in fit_transform
    self.fit(X, **params)
  File "...\Anaconda3\envs\...\lib\site-packages\sklearn\base.py", line 1152, in wrapper
    return fit_method(estimator, *args, **kwargs)
  File "...\Anaconda3\envs\...\lib\site-packages\sklearn\decomposition\_kernel_pca.py", line 437, in fit
    self._fit_transform(K)
  File "...\Anaconda3\envs\...\lib\site-packages\sklearn\decomposition\_kernel_pca.py", line 348, in _fit_transform
    self.eigenvalues_, self.eigenvectors_ = eigsh(
  File "...\Anaconda3\envs\...\lib\site-packages\scipy\sparse\linalg\_eigen\arpack\arpack.py", line 1556, in eigsh
    if np.issubdtype(A.dtype, np.complexfloating):
  File "...\Anaconda3\envs\...\lib\site-packages\pandas\core\generic.py", line 5575, in __getattr__
    return object.__getattribute__(self, name)
AttributeError: 'DataFrame' object has no attribute 'dtype'
```

### Versions

```shell
System:
    python: 3.9.15 (main, Nov  4 2022, 16:35:55) [MSC v.1916 64 bit (AMD64)]
executable: ...\Anaconda3\envs\...\python.exe
   machine: Windows-10-10.0.22621-SP0

Python dependencies:
      sklearn: 1.3.1
          pip: 22.2.2
   setuptools: 65.5.0
        numpy: 1.21.5
        scipy: 1.9.3
       Cython: None
       pandas: 1.4.4
   matplotlib: 3.5.3
       joblib: 1.1.1
threadpoolctl: 2.2.0

Built with OpenMP: True

threadpoolctl info:
       filepath: ...\Anaconda3\envs\...\Lib\site-packages\sklearn\.libs\vcomp140.dll
         prefix: vcomp
       user_api: openmp
   internal_api: openmp
        version: None
    num_threads: 8

       filepath: ...\Anaconda3\envs\...\Library\bin\mkl_rt.1.dll
         prefix: mkl_rt
       user_api: blas
   internal_api: mkl
        version: 2021.4-Product
    num_threads: 4
threading_layer: intel
```

COMMENT:
It is due to the fact that we don't force the output of the internal kernel centerer in the `KernelPCA` used to build the embedding.

The fix would be to set the output of the kernel centerer to `"default"`.

I will make a PR:

/take

Labels: Bug