Ask HN: Data Matching and Reconciliation machine learning algorithms suggestions

3 points by maddy1512 ↗ HN
I am trying to solve Data reconciliation problem using ML and need suggestions on which algorithm would be suitable? Follow the link to get more elaboration: https://www.kaggle.com/questions-and-answers/171307

3 comments

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You mean comparing data? For what purpose (to help assess solution) ... and why ML? Surely a rules engine is much more practical.
Umm... not comparing data but taking a data point and finding its nearest data points whose amounts nets to zero. Rule engine might work on a data where the data is not complex but here there are a lot of complexities like you don't have exact matching features which gives enough surety to rule based matching engine.
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.

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).

[0] https://en.wikipedia.org/wiki/Knapsack_problem