Ah well, the value of the threshold set depends on your data.
If your data is on the scale of 1e4 - 1e5, it is expected to provide a
really high threshold, because the sample distances are on the same scale.
We are trying to produce heuristics for an optimal "auto" threshold
parameter here, (https://github.com/scikit-learn/scikit-learn/pull/5593)
but it is under progress.
On Mon, Nov 30, 2015 at 3:10 PM, Manoj Kumar <manojkumarsivaraj...@gmail.com
> wrote:
> Hi,
>
> Can you provide your script for testing?
>
> Thanks !
>
>
>
> On Mon, Nov 30, 2015 at 3:06 PM, Dženan Softić <dzen...@gmail.com> wrote:
>
>> Hi,
>>
>> I am trying to test BIRCH with the original datasets found here:
>> https://cs.joensuu.fi/sipu/datasets/
>> (100K points, 100 clusters)
>>
>> The problem is setting the threshold. I need to set it above 10 000 to
>> get decent results. That is very weird because on BIRCH example (
>> http://scikit-learn.org/stable/auto_examples/cluster/plot_birch_vs_minibatchkmeans.html),
>> similar dataset has been produced, and with threshold set to 0.0 - 2.0
>> normal results could be obtained.
>>
>> I thought there was something wrong with the dataset itself, but then I
>> found on BIRCH issues that it was actually used for testing during the
>> development:(https://gist.github.com/MechCoder/16f121698ccd50568c2a)
>>
>> Am I doing something wrong here?
>>
>> Thanks,
>> Dzeno
>>
>>
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>
>
> --
> Manoj Kumar,
> http://manojbits.wordpress.com
> <http://goog_1017110195>
> http://github.com/MechCoder
>
--
Godspeed,
Manoj Kumar,
http://manojbits.wordpress.com
<http://goog_1017110195>
http://github.com/MechCoder
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