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I have multiple datasets with the same features, a few numerical and a few categorical. The only difference is that they are market behavior for different countries. I wanted to know if there is a way to measure similarities between two or more datasets and provide a % of similarity. For example, US and UK market behavior is 90% similar. The point of this is to identify similar markets and then use them to calculate causal impact. Please let me know what's the best way to do this.

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You can use statistical approach and try computing KL-divergence between the 2 datasets (Distributions). However, the KL-Divergence output is between 0 and ∞ (0 meaning two distributions perfectly match). Keep in mind that KL-divergence is asymmetric and not exactly a distance measure. (read more)

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