I am trying to solve Data reconciliation problem using ML and need suggestions on which algorithm would be suitable?
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https://www.kaggle.com/questions-and-answers/171307
In your example it seems the primary clue to find matches is the name, i.e. 'ABC' + Corp/Des/etc. So how about doing some fuzzy string matching? Once you have done this you can identify edge cases and additionally group by dates or whatever.<p>So you would have 'ABC' in L and a selection of matches in S. If not all of the matches in S actually belong to the ABC in L you are faced with the Knapsack Problem[0] that you can solve with different methods(sorry, no expert here).<p>[0] <a href="https://en.wikipedia.org/wiki/Knapsack_problem" rel="nofollow">https://en.wikipedia.org/wiki/Knapsack_problem</a>