Re: [MLlib] How to set Loss to Gradient Boosted Tree in Java

Thank you very much Kevin. On 29 February 2016 at 16:20, Kevin Mellott wrote: > I found a helper class that I think should do the trick. Take a look at > https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/mllib/tree/loss/Losses.scala >

Re: [MLlib] How to set Loss to Gradient Boosted Tree in Java

I found a helper class that I think should do the trick. Take a look at https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/mllib/tree/loss/Losses.scala When passing the Loss, you should be able to do something like: Losses.fromString("leastSquaresError") On Mon,

Re: [MLlib] How to set Loss to Gradient Boosted Tree in Java

It's strange as you are correct the doc does state it. But it's complaining about the constructor. When I clicked on the org.apache.spark.mllib.tree.loss.AbsoluteError class, this is what I see: @Since("1.2.0") @DeveloperApi object AbsoluteError extends Loss { /** * Method to calculate

Re: [MLlib] How to set Loss to Gradient Boosted Tree in Java

Looks like it should be present in 1.3 at org.apache.spark.mllib.tree.loss.AbsoluteError spark.apache.org/docs/1.3.0/api/java/org/apache/spark/mllib/tree/loss/AbsoluteError.html On Mon, Feb 29, 2016 at 9:46 AM, diplomatic Guru wrote: > AbsoluteError() constructor is

Re: [MLlib] How to set Loss to Gradient Boosted Tree in Java

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 wrote: > I believe that you can instantiate an instance of the AbsoluteError class > for the *Loss* object, since

Re: [MLlib] How to set Loss to Gradient Boosted Tree in Java

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

Re: [MLlib] How to set Loss to Gradient Boosted Tree in Java

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

[MLlib] How to set Loss to Gradient Boosted Tree in Java

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?