dataeval.metrics.estimators.clusterer¶

dataeval.metrics.estimators.clusterer(data)¶

Uses hierarchical clustering on the flattened data and returns clustering information.

Parameters:¶

data : ArrayLike, shape - (N, ...)¶

A dataset in an ArrayLike format. Function expects the data to have 2 or more dimensions which will flatten to (N, P) where N number of observations in a P-dimensional space.

Return type:¶

ClustererOutput

Note

The clusterer works best when the length of the feature dimension, P, is less than 500. If flattening a CxHxW image results in a dimension larger than 500, then it is recommended to reduce the dimensions.

Example

>>> clusterer(clusterer_images).clusters
array([ 2,  0,  0,  0,  0,  0,  4,  0,  3,  1,  1,  0,  2,  0,  0,  0,  0,
        4,  2,  0,  0,  1,  2,  0,  1,  3,  0,  3,  3,  4,  0,  0,  3,  0,
        3, -1,  0,  0,  2,  4,  3,  4,  0,  1,  0, -1,  3,  0,  0,  0])