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From MLnick <...@git.apache.org>
Subject [GitHub] spark pull request: [SPARK-14489][ML][PYSPARK] ALS unknown user/it...
Date Wed, 11 May 2016 17:30:09 GMT
Github user MLnick commented on a diff in the pull request:

    https://github.com/apache/spark/pull/12896#discussion_r62890571
  
    --- Diff: mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala ---
    @@ -71,6 +71,26 @@ private[recommendation] trait ALSModelParams extends Params with HasPredictionCo
     
       /** @group getParam */
       def getItemCol: String = $(itemCol)
    +
    +  /**
    +   * Param for strategy for dealing with unknown or new users/items at prediction time.
    +   * This may be useful in cross-validation or production scenarios, for handling user/item
ids
    +   * the model has not seen in the training data.
    +   * Supported values:
    +   * - "nan": predicted value for unknown ids will be NaN.
    --- End diff --
    
    Actually did think about making it case insensitive - I've seen that in
    some DT params. But figured it's probably not worth it.
    
    On Wed, 11 May 2016 at 19:24, Holden Karau <notifications@github.com> wrote:
    
    > In mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala
    > <https://github.com/apache/spark/pull/12896#discussion_r62889428>:
    >
    > > @@ -71,6 +71,26 @@ private[recommendation] trait ALSModelParams extends Params
with HasPredictionCo
    > >
    > >    /** @group getParam */
    > >    def getItemCol: String = $(itemCol)
    > > +
    > > +  /**
    > > +   * Param for strategy for dealing with unknown or new users/items at prediction
time.
    > > +   * This may be useful in cross-validation or production scenarios, for handling
user/item ids
    > > +   * the model has not seen in the training data.
    > > +   * Supported values:
    > > +   * - "nan": predicted value for unknown ids will be NaN.
    >
    > Any reason why "nan" rather than "NaN"?
    >
    > —
    > You are receiving this because you were mentioned.
    > Reply to this email directly or view it on GitHub
    > <https://github.com/apache/spark/pull/12896/files/b71dcaca39d5f10b484932eaf25e290c7796d93b#r62889428>
    >



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