Hi SPark users,
I built Random forest model by using Spark 1.6 with Java. I'm getting the
following exception:
User class threw exception: java.lang.UnsupportedOperationException:
Pipeline write will fail on this Pipeline because it contains a stage which
does not implement Writable.
Does anyon
n 10 Jan 2017 10:07 am, "Julio Antonio Soto" wrote:
>> Hi,
>>
>> I am running into OOM problems while training a Spark ML
>> RandomForestClassifier (maxDepth of 30, 32 maxBins, 100 trees).
>>
>> My dataset is arguably pretty big given the exec
You running locally? Found exactly same issue.
2 solutions:
_ reduce datA size.
_ run on EMR
Hth
On 10 Jan 2017 10:07 am, "Julio Antonio Soto" wrote:
> Hi,
>
> I am running into OOM problems while training a Spark ML
> RandomForestClassifier (maxDepth of 30, 32 maxBi
Hi,
I am running into OOM problems while training a Spark ML
RandomForestClassifier (maxDepth of 30, 32 maxBins, 100 trees).
My dataset is arguably pretty big given the executor count and size (8x5G),
with approximately 20M rows and 130 features.
The "fun fact" is tha
prediction value, or due to
waiting for future multi-class support before implementing all the
classifier methods.
On Sun, 27 Nov 2016 at 19:52 Zhiliang Zhu
wrote:
>
> Hi All,
>
> I need to print auc and prc for GBTClassifier model, it seems okay for
> RandomForestClassifier but
Hi All,
I need to print auc and prc for GBTClassifier model, it seems okay for
RandomForestClassifier but not GBTClassifier, though rawPrediction column is
neither in original data.
the codes are :
.. // Set up Pipeline val stages
= new
Hi
afaik yes (other pls override ). Generally, in RandomForest and
DecisionTree you have a column which you are trying to 'predict' (the
label) and a set of features that are used to predict the outcome.
i would assume that if you specify thelabel column and the 'features'
columns, everything else
hi ,
we have parmaters named
labelCol="labe"
,featuresCol="features",
when i precise the value here (label and features) if train my model on
data frame with other columns tha algorithme choos only label columns and
features columns ?
thanks
ing else that I'm
> missing?
>
> Thanks!
>
>
>
> --
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> Sent from the Apache Spark User Li
with the evaluator, or is there something else that I'm
missing?
Thanks!
--
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