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From Sameer Tilak <>
Subject MLLib decision tree: Weights
Date Tue, 02 Sep 2014 20:05:53 GMT

Hi everyone,
We are looking to apply a weight to each training example; this weight should be used when
computing the penalty of a misclassified example.  For instance, without weighting, each example
is penalized 1 point when evaluating the model of a classifier, such as a decision tree. 
We would like to customize this penalty for each training example, such that we could apply
a penalty of W for a misclassified example, where W is a weight associated with the given
training example.

Is this something that is supported directly in MLLib? I would appreciate if someone can point
me in right direction. 		 	   		  
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