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Hi,
While reading your code, I realized some slight differences between your algorithm in the paper and what was implemented here, and found it really difficult to understand, could you help me to clarify?
In the paper, barcodes at different values of a factor are combined by Wasserstein barycenter. However, function barymean here computes between different runs of RLT algorithm at a specific value (which are totally different because we are using witness complex). And in this repo barcodes at different values of a factor are aggregated by simple mean operator (as shown in here).
The formulation of (unsupervised) evaluation metric is $\mu = \rho_c - \rho_{\c}$, in which $\rho_c$ are summation of W distance of mean barcodes of different factor in a same cluster, and $\rho_{\c}$ are those at different clusters minus $\rho_c$. When I look at bicluster_score function, it seems to be $\rho_{\c}$ only, which makes me really confused.
The text was updated successfully, but these errors were encountered:
Hi,
While reading your code, I realized some slight differences between your algorithm in the paper and what was implemented here, and found it really difficult to understand, could you help me to clarify?
The text was updated successfully, but these errors were encountered: