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It would be nice if the KNN weights object also included a distance attribute in addition to neighbors and weights. The weights are all 1, which is not informative. In contrast, distance band weights have a binary argument, which if False gives the distance raised to a power.
I believe it would not necessitate any additional calculations. As an example, consider the GWT k-nearest neighbor weights created by GeoDa. Also, sklearn.neighbors KDTree already contains the distances.
The text was updated successfully, but these errors were encountered:
The kernel="identity" argument is not documented in the API documentation for weights.Kernel. Under libpysal.weights.Kernel class method from_dataframe there is no mention of a "kernel" argument., the argument is "function", but maybe that is something different. Please clarify the docs, that is the first point of contact for many users.
It would be nice if the KNN weights object also included a distance attribute in addition to neighbors and weights. The weights are all 1, which is not informative. In contrast, distance band weights have a binary argument, which if False gives the distance raised to a power.
I believe it would not necessitate any additional calculations. As an example, consider the GWT k-nearest neighbor weights created by GeoDa. Also, sklearn.neighbors KDTree already contains the distances.
The text was updated successfully, but these errors were encountered: