How can the labels of AgglomerativeClustering be re-computed?
One option to speedup computation with different thresholds is caching the results using the memory option.
Something like this:
from sklearn.cluster import AgglomerativeClustering

clustering = AgglomerativeClustering(compute_full_tree=True,
                                     distance_threshold=1.0,
                                     memory='mycachedir', 
                                     n_clusters=None,)