Description

This is similar to issue #9868. There might be more to find, but the gist of the issue is that the manifold learning methods that make use of nearest neigbhors algorithm should also have a parameter for metric type. Nearest Neighbors accepts these:

Valid values for metric are:

from scikit-learn: [‘cityblock’, ‘cosine’, ‘euclidean’, ‘l1’, ‘l2’, ‘manhattan’]
from scipy.spatial.distance: [‘braycurtis’, ‘canberra’, ‘chebyshev’, ‘correlation’, ‘dice’, ‘hamming’, ‘jaccard’, ‘kulsinski’, ‘mahalanobis’, ‘matching’, ‘minkowski’, ‘rogerstanimoto’, ‘russellrao’, ‘seuclidean’, ‘sokalmichener’, ‘sokalsneath’, ‘sqeuclidean’, ‘yule’]

According to the documentation

Steps/Code to Reproduce

Expected Results

Actual Results

Versions