Big Data generated by people — such as, social media posts, mobile phone GPS locations, and browsing history — provide enormous prediction value for AI systems. However, explaining how these models predict with the data remains challenging. This interesting explanation approach considers how a model would behave if it didn’t have the original set of data to work with.
Originally from KDnuggets https://ift.tt/2LElD7f
source https://365datascience.weebly.com/the-best-data-science-blog-2020/evidence-counterfactuals-for-explaining-predictive-models-on-big-data
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