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tdebatty / java-LSH

A Java implementation of Locality Sensitive Hashing (LSH)
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Dealing with missing data #12

Open LarsOL opened 7 years ago

LarsOL commented 7 years ago

I am contemplating using LSH in my application, but I am unsure how to deal with absent/missing data in a vector. The nearest neighbor imputation implies that this type of algorithm deals with this scenario, but how would I go about implementing it?

tdebatty commented 7 years ago

Hi!

I never had to test this, but my guess would be providing default values...

Le ven. 16 déc. 2016 02:34, Lars Lawoko notifications@github.com a écrit :

I am contemplating using LSH in my application, but I am unsure how to deal with absent/missing data in a vector. The nearest neighbor imputation implies that this type of algorithm deals with this scenario, but how would I go about implementing it?

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LarsOL commented 7 years ago

The main issue I see with providing a default value is that; wouldn't the values be artificially clustered around those "default" values that seem valid for the algorithm ? Random data may work, but then it is not deterministic.

Ideally what would happen is you can ignore a dimension if there is not a value in it.