I had a couple of questions:

1. I wasn't sure what to put for "See Also" section
2. line 180 is:

    return_distance : bool, default=None
        If True, return the distance between the clusters.

3. line 412 is:

    return_distance : bool, default=False
        whether or not to return the distances between the clusters.

For line 180: If it is of type bool, should that be True or False? Should the default be False, or does None imply something else?

I resolved the conflict but I think that there is still a couple of failures associated with the validation.

I resolved the conflict but I think that there is still a couple of failures associated with the validation.

This is the error, and I'm not sure where to resolve it:

E           # Errors
E           
E            - GL08: The object does not have a docstring

The full error message is:

E           ValueError: 
E           
E           None
E           
E           FeatureAgglomeration.fit_predict
E           Parsing of the method signature failed, possibly because this is a property.
E           
E           Fit the hierarchical clustering from features, or distance matrix.
E           
E           Parameters
E           ----------
E           X : array-like of shape (n_samples, n_features) or                 (n_samples, n_samples)
E               Training instances to cluster, or distances between instances if
E               ``affinity='precomputed'``.
E           
E           y : Ignored
E               Not used, present here for API consistency by convention.
E           
E           Returns
E           -------
E           labels : ndarray of shape (n_samples,)
E               Cluster labels.
E           
E           # Errors
E           
E            - GL08: The object does not have a docstring

So the problem is related to FeatureAgglomeration.fit_predict but thie GL08 error message is not consistent because this method has a docstring and is just a plain Python method (without any complex decorator or so).

@glemaitre any idea?

The None at the beginning of the error message is fishy...

This is odd, right? Instead of (n_samples, n_samples), I should have (n_samples,) ?

(not that I think that is causing the error.)

        Parameters
        ----------
        X : array-like of shape (n_samples, n_features) or \
                (n_samples, n_samples)
            Training instances to cluster, or distances between instances if
            ``affinity='precomputed'``.

This is odd, right? Instead of (n_samples, n_samples), I should have (n_samples,) ?

Nop. (n_samples, n_samples) is when we pass a distance matrix where we computed the distance between all samples and the parameter affinity="precomputed". It avoids recomputing this distance matrix internally.

This is odd, right? Instead of (n_samples, n_samples), I should have (n_samples,) ?

Nop. (n_samples, n_samples) is when we pass a distance matrix where we computed the distance between all samples and the parameter affinity="precomputed". It avoids recomputing this distance matrix internally.

Ok, it's been added back. Still not sure what is causing the error. ?

The CI for the numpydoc validation passed. So I will merge it now.

Thanks @reshamas