one question on paper: the calculation of distance matrix using by DBSCAN

[geyutang]

Dear author, Thanks for your excellent work and code release! when reading your paper, I got confused with the calculation of the distance matrix using by DBSCAN. We aim to generate self generate label by DBSCAN algorithm and I look through the DBSCAN algorithm and sklearn API. We input the distance metric or feature of unlabeled sample to the DBSCAN algorithm. In your paper, both the source feature and target feature (unlabel) are considered. Here is my question.

• the M in Algorithm1 in your paper is the inter dataset pair distance or the intra dataset pair distance?
• if the M is the inter dataset pair distance, is that we need to relabel the source data?
• if the M is the intra dataset pair distance, why we need the source data feature to calculate the target feature distance. And in Equation11 of your paper, where the paired sample from is not clear.

Thanks for your kindly reply.

[lsongx]

Hi @geyutang ,

Thanks for your interest in our paper. The M is generated by reranking. Thus, it is not a simple pair-wise distance.