Lshforest as opposed to vanilla lsh, has essentially one index time
parameter: number of copies of index. It is a rather easy space,time vs
precision parameter. We could set it heuristically to increase slowly with
data dimension, so the relative overhead decreases, and then users
shouldn't really care about parameters.
On Aug 6, 2014 5:32 PM, "Joel Nothman" <[email protected]> wrote:
> On 6 August 2014 20:04, Lars Buitinck <[email protected]> wrote:
>
>> 2014-08-06 7:52 GMT+02:00 Joel Nothman <[email protected]>:
>> > Instead, could we have an interface in which the `algorithm` parameter
>> could
>> > take any object supporting `fit(X)`, `query(X)` and `query_radius(X)`,
>> such
>> > as an LSHForest instance? Indeed you could also make 'lsh' an available
>> > algorithm using reasonable parameters automatically inferred from the
>> data,
>> > but you certainly want the user to be able to control the LSH
>> parameters.
>>
>> I'd prefer just passing strings here, though. There aren't too many
>> choices for the NN implementation, and accepting NN estimators
>> complicates the client code and the documentation. Users would have to
>> import from various places to assemble their own DBSCAN.
>>
>
> It's true that is annoying, and is one reason I suggest LSH with
> reasonable automatic parameters be available as a string.
>
>
>> If we denote NN implementations by strings + a dict for parameters, we
>> can just enumerate the various options in the docstring without the
>> need to introduce yet more conventions. This is obviously less
>> generic, but I find it unlikely that we will add large numbers of NN
>> implementations or that users will roll their own.
>>
>
> A dict is not so friendly with set_params and the grid search interface,
> if that's an issue. And I don't see why users shouldn't be able to use an
> ANN model that is more tuned to their data distribution or metric.
>
>
>
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