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From diplomatic Guru <diplomaticg...@gmail.com>
Subject Re: [MLlib] How to set Loss to Gradient Boosted Tree in Java
Date Mon, 29 Feb 2016 15:46:05 GMT
AbsoluteError() constructor is undefined.

I'm using Spark 1.3.0, maybe it is not ready for this version?



On 29 February 2016 at 15:38, Kevin Mellott <kevin.r.mellott@gmail.com>
wrote:

> I believe that you can instantiate an instance of the AbsoluteError class
> for the *Loss* object, since that object implements the Loss interface.
> For example.
>
> val loss = new AbsoluteError()
> boostingStrategy.setLoss(loss)
>
> On Mon, Feb 29, 2016 at 9:33 AM, diplomatic Guru <diplomaticguru@gmail.com
> > wrote:
>
>> Hi Kevin,
>>
>> Yes, I've set the bootingStrategy like that using the example. But I'm
>> not sure how to create and pass the Loss object.
>>
>> e.g
>>
>> boostingStrategy.setLoss(......);
>>
>> Not sure how to pass the selected Loss.
>>
>> How do I set the  Absolute Error in setLoss() function?
>>
>>
>>
>>
>> On 29 February 2016 at 15:26, Kevin Mellott <kevin.r.mellott@gmail.com>
>> wrote:
>>
>>> You can use the constructor that accepts a BoostingStrategy object,
>>> which will allow you to set the tree strategy (and other hyperparameters as
>>> well).
>>>
>>> *GradientBoostedTrees
>>> <http://spark.apache.org/docs/latest/api/java/org/apache/spark/mllib/tree/GradientBoostedTrees.html#GradientBoostedTrees(org.apache.spark.mllib.tree.configuration.BoostingStrategy)>*
>>> (BoostingStrategy
>>> <http://spark.apache.org/docs/latest/api/java/org/apache/spark/mllib/tree/configuration/BoostingStrategy.html>
>>>  boostingStrategy)
>>>
>>> On Mon, Feb 29, 2016 at 9:21 AM, diplomatic Guru <
>>> diplomaticguru@gmail.com> wrote:
>>>
>>>> Hello guys,
>>>>
>>>> I think the default Loss algorithm is Squared Error for regression, but
>>>> how do I change that to Absolute Error in Java.
>>>>
>>>> Could you please show me an example?
>>>>
>>>>
>>>>
>>>
>>
>

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