egression.
> If, generally, your predicted values are far from your actual values, then
> your model hasn't fit well. You may have a bug somewhere in your pipeline
> or you may have data without much linear relationship. Most of this isn't a
> Spark problem.
>
> On Mon, Mar 6, 2017 a
Hi All,
We are using a LinearRegressionModel in Scala. We are using a standard
StandardScaler to normalize the data before modelling.. the Code snippet
looks like this -
*Modellng - *
val labeledPointsRDD = tableRecords.map(row =>
{
val filtered = row.toSeq.filter({ case s: String => false case
Hello,
Is there a time line to add support for other model types like SVD, Cluster,
GBM etc in the subsequent releases. 1.5 Added support for Linear models only.
If there is, where can we know the tentative timeline of the same.
Thanks,
Manish
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