src.evaluation_metric.rand_index(pred_clusters: torch.Tensor, gt_classes: torch.Tensor) torch.Tensor[source]

Rand index measurement for clusters.

Rand index is computed by the number of instances predicted in the same class with the same label \(n_{11}\) and the number of instances predicted in separate classes and with different labels \(n_{00}\), normalized by the total number of instances pairs \(n(n-1)\):

\[\text{rand index} = \frac{n_{11} + n_{00}}{n(n-1)}\]
  • pred_clusters

    \((b\times n)\) predicted clusters. \(n\): number of instances.

    e.g. [[0,0,1,2,1,2]

  • gt_classes

    \((b\times n)\) ground truth classes

    e.g. [['car','car','bike','bike','person','person'],
          ['bus','bus','cat', 'sofa',  'cat',  'sofa' ]]


\((b)\) clustering purity