I'm currently confused on choosing the method for evaluating different clustering techniques. From this paper, they followed the pipeline: use Hungarian assignment for matching the cluster with true label, then calculate F1, Precision, Recall like classification problem. But other papers mentioned about Adjusted Rand Index (ARI).
I have tried both method, and I found that most of the case, the ARI give higher score than the former method. Especially, there's one case that ARI gives 0.96 score, which is close to perfect matching, but F1 gives only 0.50, which is very bad clustering.
I wonder that is there any 'official' comparison between using the two methods, and which one is more reliable/widely acknowledged?