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Further, imbalanced data exacerbates problems arising from the curse of dimensionality often found in such biological data. Insufficient training data in the minority class — In domains where datacollection is expensive, a dataset containing 10,000 examples is typically considered to be fairly large. Chawla et al.,
Implicitly, there was a prior belief about some interesting causal mechanism or an underlying hypothesis motivating the collection of the data. As computing and storage have made datacollection cheaper and easier, we now gather data without this underlying motivation. And for good reason!
Im focusing here on the environmental aspects of ESG compliance because they are the most challenging, especially in the datacollection and analysis. Most of the data for the social elements are brought together and can be reported in existing systems, especially human capital management. This is not a given.
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