Proportional sample exposures will be used as input into the
umap
function to generate a two dimensional UMAP.
create_umap(result, n_neighbors = 30, min_dist = 0.75, spread = 1)
result | A |
---|---|
n_neighbors | The size of local neighborhood used for views of
manifold approximation. Larger values result in more global the manifold,
while smaller values result in more local data being preserved.
If |
min_dist | The effective minimum distance between embedded points.
Smaller values will result in a more clustered/clumped embedding where
nearby points on the manifold are drawn closer together, while larger
values will result on a more even dispersal of points. Default |
spread | The effective scale of embedded points. In combination with
‘min_dist’, this determines how clustered/clumped the embedded points are.
Default |
A musica_result
object with a new UMAP
stored in the UMAP
slot.
See plot_umap to display the UMAP and
umap
for more information on the individual parameters
for generating UMAPs.
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