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I'm interested in that functionality and will probably make a fork.
The only difference seems to be at the level of dissimilarity evaluation. (And a few summaries, like cumulative sum of weights)
They do have test for that case that I can port to your format.
Would you be interested in that going back to main branch ? If so do you have requests / pointers ?
Api would probably be a weight array that can be empty or omitted to collapse to the current api.
Example use:
I'm interested in compressing an histogram, where x would be bin positions and w would be bins heights.
A naive approach would be to repeat the x value a number of time proportional to w,
but I work with probability so I don't have integer count.
Also this just increase time and memory complexity for nothing.
The text was updated successfully, but these errors were encountered:
The CKmean algorithm support weighted cluster.
I'm interested in that functionality and will probably make a fork.
The only difference seems to be at the level of dissimilarity evaluation. (And a few summaries, like cumulative sum of weights)
They do have test for that case that I can port to your format.
Would you be interested in that going back to main branch ? If so do you have requests / pointers ?
Api would probably be a weight array that can be empty or omitted to collapse to the current api.
Example use:
I'm interested in compressing an histogram, where x would be bin positions and w would be bins heights.
A naive approach would be to repeat the x value a number of time proportional to w,
but I work with probability so I don't have integer count.
Also this just increase time and memory complexity for nothing.
The text was updated successfully, but these errors were encountered: