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https://issues.apache.org/jira/browse/SPARK-14153?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15211781#comment-15211781
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Sean Owen commented on SPARK-14153:
-----------------------------------
It's not clear what you're doing here. You make a model on one data set, but
then evaluate it against another? that's not going to be valid at all.
> My dataset does not provide proper predictions in ALS
> -----------------------------------------------------
>
> Key: SPARK-14153
> URL: https://issues.apache.org/jira/browse/SPARK-14153
> Project: Spark
> Issue Type: Question
> Components: Java API, ML
> Reporter: Dulaj Rajitha
>
> When I used data-set in the git-hub example, I get proper predictions. But
> when I used my data set It does not predict well. (I has a large RMSE).
> I used cross validator for ALS (in Spark ML) and here are the best model
> parameters.
> 16/03/25 12:03:06 INFO CrossValidator: Average cross-validation metrics:
> WrappedArray(NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN)
> 16/03/25 12:03:06 INFO CrossValidator: Best set of parameters:
> {
> als_c911c0e183a3-alpha: 0.02,
> als_c911c0e183a3-rank: 500,
> als_c911c0e183a3-regParam: 0.03
> }
> But when I used movie data set It gives proper values for parameters. as below
> 16/03/24 14:07:07 INFO CrossValidator: Average cross-validation metrics:
> WrappedArray(1.9481584447713676, 2.0501457159728944, 2.0600857505406935,
> 1.9457234533860048, 2.0494498583414282, 2.0595306613827002,
> 1.9488322049918922, 2.0489573853226797, 2.0584252131752, 1.9464006741621391,
> 2.048241271354197, 2.057853990227443)
> 16/03/24 14:07:07 INFO CrossValidator: Best set of parameters:
> {
> als_31a605e7717b-alpha: 0.02,
> als_31a605e7717b-rank: 1,
> als_31a605e7717b-regParam: 0.02
> }
> 16/03/24 14:07:07 INFO CrossValidator: Best cross-validation metric:
> 1.9457234533860048.
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