[jira] [Updated] (SPARK-3903) Create general data loading method for LabeledPoints

2015-04-20 Thread Joseph K. Bradley (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-3903?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Joseph K. Bradley updated SPARK-3903:
-
Affects Version/s: (was: 1.1.0)
   1.3.0

> 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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[jira] [Updated] (SPARK-3903) Create general data loading method for LabeledPoints

2015-04-20 Thread Joseph K. Bradley (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-3903?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Joseph K. Bradley updated SPARK-3903:
-
Component/s: (was: MLlib)
 ML

> 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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[jira] [Updated] (SPARK-3903) Create general data loading method for LabeledPoints

2015-04-20 Thread Joseph K. Bradley (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-3903?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Joseph K. Bradley updated SPARK-3903:
-
Assignee: (was: Joseph K. Bradley)

> 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: MLlib
>Affects Versions: 1.1.0
>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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[jira] [Updated] (SPARK-3903) Create general data loading method for LabeledPoints

2015-04-20 Thread Joseph K. Bradley (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-3903?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Joseph K. Bradley updated SPARK-3903:
-
Affects Version/s: 1.1.0

> 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: MLlib
>Affects Versions: 1.1.0
>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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[jira] [Updated] (SPARK-3903) Create general data loading method for LabeledPoints

2014-10-10 Thread Xiangrui Meng (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-3903?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Xiangrui Meng updated SPARK-3903:
-
Assignee: Joseph K. Bradley

> 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: MLlib
>Reporter: Joseph K. Bradley
>Assignee: 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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[jira] [Updated] (SPARK-3903) Create general data loading method for LabeledPoints

2014-10-10 Thread Joseph K. Bradley (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-3903?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Joseph K. Bradley updated SPARK-3903:
-
Description: 
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


  was:
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



> 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: MLlib
>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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