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.
