And what about the number of trees?
On Wed, Aug 6, 2014 at 9:55 PM, Maheshakya Wijewardena <
[email protected]> wrote:
> Actually in our implementation of LSH Forest, we have an extra parameter
> to control the candidate acquisition(to avoid having the candidates with
> very small hash length matches - lower bound for max_depth) for
> `kneighbors` queries. But that too could be controlled by some heuristic
> method.
>
> But in DBSCAN, we're considering the radius neighbors which is quite
> different from finding K nearest neighbors. The parameter we have to
> consider here is actual_radius_neighbors to candidates ratio(Here also that
> lower bound parameter is required). Can we use a heuristic based method to
> determine that ratio parameter as well?
>
>
> On Wed, Aug 6, 2014 at 9:38 PM, Daniel Vainsencher <
> [email protected]> wrote:
>
>> 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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>
>
> --
> Undergraduate,
> Department of Computer Science and Engineering,
> Faculty of Engineering.
> University of Moratuwa,
> Sri Lanka
>
--
Undergraduate,
Department of Computer Science and Engineering,
Faculty of Engineering.
University of Moratuwa,
Sri Lanka
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