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Posted to dev@spark.apache.org by DB Tsai <db...@dbtsai.com> on 2014/12/12 20:37:05 UTC
CrossValidator API in new spark.ml package
Hi Xiangrui,
It seems that it's stateless so will be hard to implement
regularization path. Any suggestion to extend it? Thanks.
Sincerely,
DB Tsai
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Re: CrossValidator API in new spark.ml package
Posted by Xiangrui Meng <me...@gmail.com>.
Yes, regularization path could be viewed as training multiple models
at once. -Xiangrui
On Sat, Dec 13, 2014 at 6:53 AM, DB Tsai <db...@dbtsai.com> wrote:
> Okay, I got it. In Estimator, fit(dataset: SchemaRDD, paramMaps:
> Array[ParamMap]): Seq[M] can be overwritten to implement
> regularization path. Correct me if I'm wrong.
>
> Sincerely,
>
> DB Tsai
> -------------------------------------------------------
> My Blog: https://www.dbtsai.com
> LinkedIn: https://www.linkedin.com/in/dbtsai
>
>
> On Fri, Dec 12, 2014 at 11:37 AM, DB Tsai <db...@dbtsai.com> wrote:
>> Hi Xiangrui,
>>
>> It seems that it's stateless so will be hard to implement
>> regularization path. Any suggestion to extend it? Thanks.
>>
>> Sincerely,
>>
>> DB Tsai
>> -------------------------------------------------------
>> My Blog: https://www.dbtsai.com
>> LinkedIn: https://www.linkedin.com/in/dbtsai
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Re: CrossValidator API in new spark.ml package
Posted by DB Tsai <db...@dbtsai.com>.
Okay, I got it. In Estimator, fit(dataset: SchemaRDD, paramMaps:
Array[ParamMap]): Seq[M] can be overwritten to implement
regularization path. Correct me if I'm wrong.
Sincerely,
DB Tsai
-------------------------------------------------------
My Blog: https://www.dbtsai.com
LinkedIn: https://www.linkedin.com/in/dbtsai
On Fri, Dec 12, 2014 at 11:37 AM, DB Tsai <db...@dbtsai.com> wrote:
> Hi Xiangrui,
>
> It seems that it's stateless so will be hard to implement
> regularization path. Any suggestion to extend it? Thanks.
>
> Sincerely,
>
> DB Tsai
> -------------------------------------------------------
> My Blog: https://www.dbtsai.com
> LinkedIn: https://www.linkedin.com/in/dbtsai
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