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negative gap values #44
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This is due to #38, which has been fixed recently. |
thanks for your reply.
also, I was wondering if the new implementation would just turn negative values to the same positive values, or the generated values will be different? |
The Rust part has not been fixed yet, please use the default parallel backend "joblib". The positive values will be completely different. As for the optimal number of clusters, I believe that depends on the data. In my case, the outcome didn't change much. However, it was very important to increase the number of reference datasets and use a custom clusterer to obtain stable results. |
Going to close this as the Rust side is fixed now. After CI finished you can do |
Can someone please explain why gap values in this implementation are negative?
Based on the formulas in the paper, a negative gap value means that distances in random clusterings are smaller than the original clustering => random ones are better than the original one. I have verified that in another book as well.
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