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https://issues.apache.org/jira/browse/SPARK-6948?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15394190#comment-15394190
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Sean Owen commented on SPARK-6948:
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I tend to agree, ran into this just recently in the exact same context. It was
surprising when a tiny vector was made sparse and then not usable with
StandardScaler (with "subtract mean" enabled).
> VectorAssembler should choose dense/sparse for output based on number of zeros
> ------------------------------------------------------------------------------
>
> Key: SPARK-6948
> URL: https://issues.apache.org/jira/browse/SPARK-6948
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Affects Versions: 1.4.0
> Reporter: Xiangrui Meng
> Assignee: Xiangrui Meng
> Priority: Minor
> Fix For: 1.4.0
>
>
> Now VectorAssembler only outputs sparse vectors. We should choose
> dense/sparse format automatically, whichever uses less memory.
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