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Hi, in the original paper by Berman, he states the use of the KL Divergence as the metric to compare two points (wavelet coefficients). Did you achieve any success with using the "symmetric_kl" metric in UMAP? Secondly, I get very poor performance for my behaviour data using the wavelets, even after subsampling the original data. Do you have any suggestions how to improve the same? I have keypoint data (identified by DeepLabCut) at a sampling rate of 30Hz.
The text was updated successfully, but these errors were encountered:
Hi, in the original paper by Berman, he states the use of the KL Divergence as the metric to compare two points (wavelet coefficients). Did you achieve any success with using the "symmetric_kl" metric in UMAP? Secondly, I get very poor performance for my behaviour data using the wavelets, even after subsampling the original data. Do you have any suggestions how to improve the same? I have keypoint data (identified by DeepLabCut) at a sampling rate of 30Hz.
The text was updated successfully, but these errors were encountered: