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https://issues.apache.org/jira/browse/SPARK-6340?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Kian Ho updated SPARK-6340:
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Description:
as per:
http://apache-spark-user-list.1001560.n3.nabble.com/Using-TF-IDF-from-MLlib-td19429.html#a19528
Having the IDF.fit accept LabelPoints would be useful since, correct me if i'm
wrong, there currently isn't a way of keeping track of which labels belong to
which documents if one needs to apply a conventional tf-idf transformation on
labelled text data.
was:
as per:
http://apache-spark-user-list.1001560.n3.nabble.com/Using-TF-IDF-from-MLlib-td19429.html#a19528
Having the IDF.fit accept LabelPoints would be useful since, correct me if i'm
wrong, there currently isn't a way of keeping track of which labels belong to
which documents if one needs to apply a conventional tf-idf transformation on
text data.
> mllib.IDF for LabelPoints
> -------------------------
>
> Key: SPARK-6340
> URL: https://issues.apache.org/jira/browse/SPARK-6340
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Affects Versions: 1.3.0
> Environment: python 2.7.8
> pyspark
> OS: Linux Mint 17 Qiana (Cinnamon 64-bit)
> Reporter: Kian Ho
> Priority: Minor
> Labels: feature
>
> as per:
> http://apache-spark-user-list.1001560.n3.nabble.com/Using-TF-IDF-from-MLlib-td19429.html#a19528
> Having the IDF.fit accept LabelPoints would be useful since, correct me if
> i'm wrong, there currently isn't a way of keeping track of which labels
> belong to which documents if one needs to apply a conventional tf-idf
> transformation on labelled text data.
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