pnnl/DDKS
A high-dimensional Kolmogorov-Smirnov distance for comparing high dimensional distributions
This tool helps scientists and data analysts compare if two high-dimensional datasets come from the same underlying process, like comparing different experimental batches or simulated outcomes. It takes in two collections of data points, each with many measurements, and outputs a single number indicating how different their overall patterns are. Researchers in fields like physics, chemistry, or bioinformatics would use this to validate models or ensure data consistency.
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Use this if you need to statistically compare two datasets to determine if they originated from identical high-dimensional distributions, especially when traditional methods struggle with many variables.
Not ideal if your data has only a few dimensions or if you need to identify specific feature differences between the datasets rather than just a general dissimilarity score.
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Last pushed
Sep 20, 2022
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