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https://issues.apache.org/jira/browse/SPARK-3903?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15960531#comment-15960531
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Nick Pentreath commented on SPARK-3903:
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I think given the move to DataFrames, and that we can load {{libsvm}} in DF,
this can be closed?
> Create general data loading method for LabeledPoints
> ----------------------------------------------------
>
> Key: SPARK-3903
> URL: https://issues.apache.org/jira/browse/SPARK-3903
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Affects Versions: 1.3.0
> Reporter: Joseph K. Bradley
> Priority: Minor
>
> Proposal: Provide a more general data loading function for LabeledPoints.
> * load multiple data files (e.g., train + test), and ensure they have the
> same number of features (determined based on a scan of the data)
> * use same function for multiple input formats
> Proposed function format (in MLUtils), with default parameters:
> {code}
> def loadLabeledPointsFiles(
> sc: SparkContext,
> paths: Seq[String],
> numFeatures = -1,
> vectorFormat = "auto",
> numPartitions = sc.defaultMinPartitions): Seq[RDD[LabeledPoint]]
> {code}
> About the parameters:
> * paths: list of paths to data files or folders with data files
> * vectorFormat options: dense/sparse/auto
> * numFeatures, numPartitions: same behavior as loadLibSVMFile
> Return value: Order of RDDs follows the order of the paths.
> Note: This is named differently from loadLabeledPoints for 2 reasons:
> * different argument order (following loadLibSVMFile)
> * different return type
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