angrui Meng [mailto:men...@gmail.com]
Sent: Tuesday, 10 February 2015 7:07 AM
To: Christopher Thom
Cc: user@spark.apache.org
Subject: Re: [MLlib] Performance issues when building GBM models
Could you check the Spark UI and see whether there are RDDs being kicked out
during the computation? We cache the
nt at
DecisionTreeMetadata.scala:111, took 5.495166 s
Any thoughts or advice, or even suggestions on where to dig for more info would
be welcome.
thanks
chris
Christopher Thom
QUANTIUM
Level 25, 8 Chifley, 8-12 Chifley Square
Sydney NSW 2000
T: +61 2 8222 3577
F: +61 2 9292 6444
W: quantium.c
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imal" when the MSE is minimum. i.e. in a plot of MSE vs
Number of trees, the error rate will decrease (as the model improves), hit a
minimum (the optimal point), and then increase (as the model starts to overfit
the data).
cheers
chris
Christopher Thom
QUANTIUM
Level 25, 8 Chifley, 8-12
ay, 6 January 2015 8:43 AM
To: Christopher Thom
Cc: user@spark.apache.org
Subject: Re: python API for gradient boosting?
I created a JIRA for it:
https://issues.apache.org/jira/browse/SPARK-5094. Hopefully someone would work
on it and make it available in the 1.3 release. -Xiangrui
On Sun, Jan 4,
compelling.
As an alternative, if it'll be a while before this API is implemented, does
anyone have suggestions for scala replacements for the above python libraries?
cheers
chris
Christopher Thom
QUANTIUM
Level 25, 8 Chifley, 8-12 Chifley Square
Sydney NSW 2000
T: +61 2 8222 3577
F: +61 2 9292 64
Hi,
I wonder if anyone knows when a python API will be added for Gradient Boosted
Trees? I see that java and scala APIs were added for the 1.2 release, and would
love to be able to build GBMs in pyspark too.
cheers
chris
Christopher Thom
QUANTIUM
Level 25, 8 Chifley, 8-12 Chifley Square
