Hello.
2020-03-07 14:50 UTC+01:00, chentao...@qq.com :
> Hi,
>
>>> > [...]
>>> Solution 3 is "ClusterRanking".
>>> In cases where the reference algorithm would assume the
>>> other convention (i.e. "lower is better"), the implementation
>>> is required to apply a conversion (e.g. return the oppo
Hi,
>> > [...]
>> Solution 3 is "ClusterRanking".
>> In cases where the reference algorithm would assume the
>> other convention (i.e. "lower is better"), the implementation
>> is required to apply a conversion (e.g. return the opposite).
>
>s/opposite/inverse/
>
>[We should probably enforce tha
Hi,
>Hello.
>
[...]
>> For machine learning centroid cluster algorithm, we often use is
>> Calinsk-iHarabasz score to evaluate which algorithm or how many
>> centers is
>> best for a dataset.
>> The python lib sklearn implements Calinsk-iHarabasz as
>> sk
> > [...]
> Solution 3 is "ClusterRanking".
> In cases where the reference algorithm would assume the
> other convention (i.e. "lower is better"), the implementation
> is required to apply a conversion (e.g. return the opposite).
s/opposite/inverse/
[We should probably enforce that ranking is p
Hello.
>>> [...]
>>> >> For machine learning centroid cluster algorithm, we often use is
>>> >> Calinsk-iHarabasz score to evaluate which algorithm or how many
>>> >> centers is
>>> >> best for a dataset.
>>> >> The python lib sklearn implements Calinsk-iHarabasz as
>>> >> sklearn.metrics.
Hi,
>Le ven. 6 mars 2020 à 14:35, chentao...@qq.com a écrit :
>>
>> Hi,
>>
>> >Hello.
>> >
>> >2020-03-06 9:48 UTC+01:00, chentao...@qq.com :
>> >> Hi,
>> >> For machine learning centroid cluster algorithm, we often use is
>> >> Calinsk-iHarabasz score to evaluate which algorithm or how many
Le ven. 6 mars 2020 à 14:35, chentao...@qq.com a écrit :
>
> Hi,
>
> >Hello.
> >
> >2020-03-06 9:48 UTC+01:00, chentao...@qq.com :
> >> Hi,
> >> For machine learning centroid cluster algorithm, we often use is
> >> Calinsk-iHarabasz score to evaluate which algorithm or how many centers is
> >>
Hi,
>Hello.
>
>2020-03-06 9:48 UTC+01:00, chentao...@qq.com :
>> Hi,
>> For machine learning centroid cluster algorithm, we often use is
>> Calinsk-iHarabasz score to evaluate which algorithm or how many centers is
>> best for a dataset.
>> The python lib sklearn implements Calinsk-iHaraba
Hello.
2020-03-06 9:48 UTC+01:00, chentao...@qq.com :
> Hi,
> For machine learning centroid cluster algorithm, we often use is
> Calinsk-iHarabasz score to evaluate which algorithm or how many centers is
> best for a dataset.
> The python lib sklearn implements Calinsk-iHarabasz as
> sklea
