# src.evaluation_metric.rand_index¶

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 $$n(n-1)$$:

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

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

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


• gt_classes

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

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


Returns

$$(b)$$ clustering purity