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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-9664) FlinkML Quickstart Loading Data section example doesn't work as described
Date Wed, 08 Aug 2018 13:23:00 GMT

    [ https://issues.apache.org/jira/browse/FLINK-9664?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16573225#comment-16573225
] 

ASF GitHub Bot commented on FLINK-9664:
---------------------------------------

azagrebin 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_r208576999
 
 

 ##########
 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 think this section belongs to the beginning of the next one `Classification`, because
this one is about LibSVM format.
   The code example of conversion could be also provided to make the example fully 'copy-paste'
runnable.
   Small thing is also typo in `traning` -> `training`.
   
   I would suggest to modify the code example in this `LibSVM files` section like this:
   ```
   val astroTrainLibSVM: DataSet[LabeledVector] = MLUtils.readLibSVM(env, "/path/to/svmguide1")
   val astroTestLibSVM: DataSet[LabeledVector] = MLUtils.readLibSVM(env, "/path/to/svmguide1.t")
   ```
   to have no SVM training specifics here, and add something like this to the beginning of
the `Classification` section:
   
   _... After importing the training and test dataset, the data needs to be prepared for the
classification, because Flink SVM only supports ... conversion is needed after downloading
..._
   And then the code example:
   ```
   def svmNormaliser : LabeledVector => LabeledVector =
       lv => LabeledVector(if (lv.label > 0.0) 1.0 else -1.0, lv.vector)
   val astroTrain: DataSet[LabeledVector] = astroTrainLibSVM.map(svmNormaliser)
   val astroTest: DataSet[(Vector, Double)] = astroTestLibSVM.map(svmNormaliser).map(x =>
(x.vector, x.label))
   ```

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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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