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https://issues.apache.org/jira/browse/FLINK-9664?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16573377#comment-16573377
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ASF GitHub Bot commented on FLINK-9664:
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walterddr commented on a change in pull request #6425: [FLINK-9664][Doc] fixing
documentation in ML quick start
URL: https://github.com/apache/flink/pull/6425#discussion_r208629086
##########
File path: docs/dev/libs/ml/quickstart.md
##########
@@ -129,6 +129,10 @@ and the [test set
here](http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/b
This is an astroparticle binary classification dataset, used by Hsu et al.
[[3]](#hsu) in their
practical Support Vector Machine (SVM) guide. It contains 4 numerical
features, and the class label.
+Before importing the traning and test dataset, Flink SVM only supports
threshold binary values of
+`+1.0` and `-1.0`. Thus a conversion is needed upon downloading the svmguide1
dataset since it is
+labelled using `1`s and `0`s.
+
Review comment:
I see. if i understand correctly, summary of the suggestions are:
1. move the explanation of why -1.0 and +1.0 to classification page.
2. leave the quickstart section clean by adding an explicit conversion from
0,1 to -1,1 so that copy-paste will work. and do not expand too much into why
-1,+1 is needed, just mentioned that's needed.
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> FlinkML Quickstart Loading Data section example doesn't work as described
> -------------------------------------------------------------------------
>
> Key: FLINK-9664
> URL: https://issues.apache.org/jira/browse/FLINK-9664
> Project: Flink
> Issue Type: Bug
> Components: Documentation, Machine Learning Library
> Affects Versions: 1.5.0
> Reporter: Mano Swerts
> Assignee: Rong Rong
> Priority: Major
> Labels: documentation-update, machine_learning, ml,
> pull-request-available
> Original Estimate: 1h
> Remaining Estimate: 1h
>
> The ML documentation example isn't complete:
> [https://ci.apache.org/projects/flink/flink-docs-release-1.5/dev/libs/ml/quickstart.html#loading-data]
> The referred section loads data from an astroparticle binary classification
> dataset to showcase SVM. The dataset uses 0 and 1 as labels, which doesn't
> produce correct results. The SVM predictor expects -1 and 1 labels to
> correctly predict the label. The documentation, however, doesn't mention
> that. The example therefore doesn't work without a clue why.
> The documentation should be updated with an explicit mention to -1 and 1
> labels and a mapping function that shows the conversion of the labels.
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