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https://issues.apache.org/jira/browse/FLINK-4438?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Robert Metzger updated FLINK-4438:
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Component/s: Library / Machine Learning
> FlinkML Quickstart Guide implies incorrect type for test data
> -------------------------------------------------------------
>
> Key: FLINK-4438
> URL: https://issues.apache.org/jira/browse/FLINK-4438
> Project: Flink
> Issue Type: Bug
> Components: Documentation, Library / Machine Learning
> Affects Versions: 1.2.0
> Reporter: Ahmad Ragab
> Priority: Minor
>
> https://ci.apache.org/projects/flink/flink-docs-master/apis/batch/libs/ml/quickstart.html
> Documentation under *LibSVM* section says that:
> ----
> We can simply import the dataset then using:
> {code:java}
> import org.apache.flink.ml.MLUtils
> val astroTrain: DataSet[LabeledVector] =
> MLUtils.readLibSVM("/path/to/svmguide1")
> val astroTest: DataSet[LabeledVector] =
> MLUtils.readLibSVM("/path/to/svmguide1.t")
> {code}
> This gives us two {{DataSet\[LabeledVector\]}} objects that we will use in
> the following section to create a classifier.
> ----
> Test data wouldn't be of type {{LabeledVector}} generally, it would be as it
> is described in other examples as {{DataSet\[Vector\]}} since prediction
> should generate the labels. Thus after reading the file using {{MLUtils}} it
> should be mapped to a vector.
> Also, the previous section in *Loading Data* should include an example of
> using the {{Splitter}} in order to prepare the {{survivalLV}} data for use
> with a learner.
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