The indexing I mentioned is more restrictive than that: each index
corresponds to a unique position in a binary tree. (I.e., the first index
of row 0 is 1, the first of row 1 is 2, the first of row 2 is 4, etc., IIRC)
You're correct that this restriction could be removed; with some careful
though
Hi, Joseph,
I thought I understood, why it has a limit of 30 levels for decision tree,
but now I'm not that sure. I thought that's because the decision tree
stored in the array, which has length of type int, which cannot be more,
than 2^31-1.
But here are my new discoveries. I've trained two diffe
3 AM
> *To:* Joseph Bradley
> *Cc:* Eugene Morozov; user; dev@spark.apache.org
> *Subject:* Re: SparkML algos limitations question.
>
>
>
> Hi Eugene,
>
>
>
> AFAIK, the current implementation of MultilayerPerceptronClassifier have
> some scalability problems if the m
regards, Alexander
From: Yanbo Liang [mailto:yblia...@gmail.com]
Sent: Sunday, December 27, 2015 2:23 AM
To: Joseph Bradley
Cc: Eugene Morozov; user; dev@spark.apache.org
Subject: Re: SparkML algos limitations question.
Hi Eugene,
AFAIK, the current implementation of MultilayerPerceptronClassifier have
Hi Eugene,
AFAIK, the current implementation of MultilayerPerceptronClassifier have
some scalability problems if the model is very huge (such as >10M),
although I think the limitation can cover many use cases already.
Yanbo
2015-12-16 6:00 GMT+08:00 Joseph Bradley :
> Hi Eugene,
>
> The maxDept
Hi Eugene,
The maxDepth parameter exists because the implementation uses Integer node
IDs which correspond to positions in the binary tree. This simplified the
implementation. I'd like to eventually modify it to avoid depending on
tree node IDs, but that is not yet on the roadmap.
There is not
Hello!
I'm currently working on POC and try to use Random Forest (classification
and regression). I also have to check SVM and Multiclass perceptron (other
algos are less important at the moment). So far I've discovered that Random
Forest has a limitation of maxDepth for trees and just out of curi
