Ahmad Ragab created FLINK-4438:
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Summary: 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
Affects Versions: 1.2.0
Reporter: Ahmad Ragab
Priority: Minor
Fix For: 1.2.0
https://ci.apache.org/projects/flink/flink-docs-master/apis/batch/libs/ml/quickstart.html
Documentation under *LibSVM* section says that:
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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.
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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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