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What is the approach to estimate cross-price elasticity of a large number of products fe. 50000 using machine learning?

Assuming that we have transactional data of a retailer with big number of active products (about 50 000) and the capacity of  our machine learning model is limited, is there any good way to deal with such large dataset?
For example any good approach to somehow split the data into categories, subcategories, segments? Do you have any reference?

Thank you in advance
asked Jan 19 by Phil

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