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to each compressor and seeing which compressor yields the highest compression. The coder with the best compression is probably the coder trained on the data that was most similar to the unknown data. This approach is grounded in the concept of normalized compression distance, a parameter-free, universal similarity metric based on compression that approximates the uncomputable normalized information distance.