On Sun, Jan 11, 2015 at 9:46 PM, Christopher Thom
wrote:
> Is there any plan to extend the data types that would be accepted by the Tree
> models in Spark? e.g. Many models that we build contain a large number of
> string-based categorical factors. Currently the only strategy is to map these
>
Sent: Sunday, 11 January 2015 10:53 PM
To: Carter
Cc: user@spark.apache.org
Subject: Re: Does DecisionTree model in MLlib deal with missing values?
I do not recall seeing support for missing values.
Categorical values are encoded as 0.0, 1.0, 2.0, ... When training the model
you indicate which are i
int requires
> "double" data type, in this case what can I do?
>
> Thank you very much.
>
>
>
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> Sent fro
very much.
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