[jira] [Commented] (SPARK-19382) Test sparse vectors in LinearSVCSuite

["Miao Wang (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-19382?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15850369#comment-15850369 ] 

Miao Wang commented on SPARK-19382:
-----------------------------------

In addition,

 def merge(other: MultivariateOnlineSummarizer): this.type = {
    if (this.totalWeightSum != 0.0 && other.totalWeightSum != 0.0) {
      require(n == other.n, s"Dimensions mismatch when merging with another summarizer. " +
        s"Expecting $n but got ${other.n}.")

So mixed DenseVector and SparseVector will throw the above exception, `Dimensions mismatch when merging with another summarizer.` due to the finding in the previous reply.

I will create separate test cases for SparseVector. Thanks!



> Test sparse vectors in LinearSVCSuite
> -------------------------------------
>
>                 Key: SPARK-19382
>                 URL: https://issues.apache.org/jira/browse/SPARK-19382
>             Project: Spark
>          Issue Type: Test
>          Components: ML
>            Reporter: Joseph K. Bradley
>            Priority: Minor
>
> Currently, LinearSVCSuite does not test sparse vectors.  We should.  I recommend that generateSVMInput be modified to create a mix of dense and sparse vectors, rather than adding an additional test.



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