Documentation of metric handling.
@@ -726,8 +726,12 @@ class UMAP(BaseEstimator):
* euclidean
* manhattan
* chebyshev
+ * minkowski
* canberra
* braycurtis
+ * mahalanobis
+ * wminkowski
+ * seuclidean
* cosine
* correlation
* haversine
@@ -740,6 +744,10 @@ class UMAP(BaseEstimator):
* sokalmichener
* sokalsneath
* yule
+ Metrics that take arguments (such as minkowski, mahalanobis etc.)
+ can have arguments passed via the metric_kwds dictionary. At this
+ time care must be taken and dictionary elements must be ordered
+ appropriately; this will hopefully be fixed in the future.
gamma: float (optional, default 1.0)
Weighting applied to negative samples in low dimensional embedding
@@ -781,10 +789,9 @@ class UMAP(BaseEstimator):
values are set automatically as determined by ``min_dist`` and
``spread``.
- oversampling: int (optional, default 3)
- The scaling factor for the number of neighbors to sample to attempt
- to find the local neighborhood in manifold distance. If set to be too
- large this can have a significant negative impact on performance.
+ metric_kwds: dict (optional, default {})
+ Arguments to pass on to the metric, such as the ``p`` value for
+ Minkowski distance.
"""
def __init__(self,
