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https://issues.apache.org/jira/browse/FLINK-3330?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15133990#comment-15133990
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ASF GitHub Bot commented on FLINK-3330:
---------------------------------------
Github user tillrohrmann commented on a diff in the pull request:
https://github.com/apache/flink/pull/1587#discussion_r52001534
--- Diff:
flink-libraries/flink-ml/src/test/scala/org/apache/flink/ml/regression/RegressionData.scala
---
@@ -27,6 +27,21 @@ object RegressionData {
val expectedWeight0: Double = 9.8158
val expectedSquaredResidualSum: Double = 49.7596/2
+ val sparseData: Seq[LabeledVector] = Seq(
+ new LabeledVector(1.0, new SparseVector(10, Array(0, 2, 3), Array(1.0,
1.0, 1.0))),
+ new LabeledVector(1.0, new SparseVector(10, Array(0, 1, 5, 9),
Array(1.0, 1.0, 1.0, 1.0))),
+ new LabeledVector(0.0, new SparseVector(10, Array(0, 2), Array(0.0,
1.0))),
+ new LabeledVector(0.0, new SparseVector(10, Array(0), Array(0.0))),
+ new LabeledVector(0.0, new SparseVector(10, Array(0, 2), Array(0.0,
1.0))),
+ new LabeledVector(0.0, new SparseVector(10, Array(0), Array(0.0))))
+
+ val expectedWeightsSparseInput = Array(0.5448906338353784,
0.15718880164669916,
+ 0.034001300318125725,
0.38770183218867915, 0.0,
+ 0.15718880164669916, 0.0, 0.0,
0.0, 0.15718880164669916)
--- End diff --
Will fix it.
> Add SparseVector support to GradientDescent in FlinkML
> ------------------------------------------------------
>
> Key: FLINK-3330
> URL: https://issues.apache.org/jira/browse/FLINK-3330
> Project: Flink
> Issue Type: Improvement
> Components: Machine Learning Library
> Affects Versions: 1.0.0
> Reporter: Chiwan Park
> Assignee: Till Rohrmann
>
> A user reported the problem using {{GradientDescent}} algorithm with
> {{SparseVector}}.
> (http://mail-archives.apache.org/mod_mbox/flink-user/201602.mbox/%3CCAMJxVsiNRy_B349tuRpC%2BY%2BfyW7j2SHcyVfhqnz3BGOwEHXHpg%40mail.gmail.com%3E)
> It seems lack of SparseVector support in {{BLAS.axpy}}.
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