... | @@ -15,6 +15,18 @@ In some datasets, this procedure may be of considerable complexity and we need t |
... | @@ -15,6 +15,18 @@ In some datasets, this procedure may be of considerable complexity and we need t |
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Another important matter here is the distance. The CC works with *common* distance metrics, such as the `cosine` or `euclidean` distances. Sometimes, connectivity may require other types of metrics (e.g. GSEA-like, overlap, etc.). We might consider learning siamese networks that transform original distances to the more standard ones. This is an unexplored avenue, though.
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Another important matter here is the distance. The CC works with *common* distance metrics, such as the `cosine` or `euclidean` distances. Sometimes, connectivity may require other types of metrics (e.g. GSEA-like, overlap, etc.). We might consider learning siamese networks that transform original distances to the more standard ones. This is an unexplored avenue, though.
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