CSVIterator

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1. final def !=(arg0: Any): Boolean

   

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2. final def ##(): Int

   

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3. final def ==(arg0: Any): Boolean

   

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8. def finalize(): Unit

   

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9. def fromPlainCSV(filePath: String, numLinesToSkip: Int = 1, delimiter: Char = CSVRecordReader.DEFAULT_DELIMITER, quote: Char = CSVRecordReader.DEFAULT_QUOTE, batchSize: Int = 128, classification: Boolean = false, labelIndex: Int = 0, numPossibleLabels: Int = 2, regression: Boolean = false, labelIndexTo: Int = 0, seed: Long = 2018L): RecordReaderDataSetIterator

   

   Columnar CSV file

   Columnar CSV file

   filePath

   file name path

   numLinesToSkip

   number of lines to skip, default=1

   delimiter

   delimiter, default=','. Other options:

   '\t': for tab-delimitd
   CSVRecordReader.QUOTE_HANDLING_DELIMITER: for records containing quotes with commas in them

   quote

   quote, default='\"'

   batchSize

   batch size, default=128

   classification

   whether for classification, default=false

   labelIndex

   label index when classification=true, default=0

   numPossibleLabels

   label cardinality when classification=true, default=2

   regression

   whether for regression, default=false

   labelIndexTo

   only for regression, the last index (inclusive) for multi-output regression, default=0

   returns

   dataset iterator

10. def fromPlainCSV0(filePath: String, numLinesToSkip: Int = 1, delimiter: Char = CSVRecordReader.DEFAULT_DELIMITER, quote: Char = CSVRecordReader.DEFAULT_QUOTE, batchSize: Int = 128, classification: Boolean = false, labelIndex: Int = 0, numPossibleLabels: Int = 2, regression: Boolean = false, labelIndexTo: Int = 0, seed: Long = 2018L): RecordReaderDataSetIterator

    

11. def fromPlainCSVWithSchema(filePath: String, columnNameTypes: Array[(String, String)], columnCategoricalValues: Map[String, Array[String]] = Map(), removeColumns: Array[String] = Array(), categorical2OneHots: Array[String] = Array(), categorical2Ints: Array[String] = Array(), numLinesToSkip: Int = 1, delimiter: Char = CSVRecordReader.DEFAULT_DELIMITER, quote: Char = CSVRecordReader.DEFAULT_QUOTE, batchSize: Int = 128, classification: Boolean = false, labelIndex: Int = 0, numPossibleLabels: Int = 2, regression: Boolean = false, labelIndexTo: Int = 0, seed: Long = 2018L): RecordReaderDataSetIterator

    

    Columnar CSV file

    Columnar CSV file

    filePath

    file name path

    columnNameTypes

    columm name and types, preserving the order of the input files types: "double", "float", "long", "integer", "string", "categorical" (must provide the value list).

    columnCategoricalValues

    categorical column values

    removeColumns

    columns to ignore

    categorical2OneHots

    columns to transform to one-hots

    categorical2Ints

    columns to transform to ints

    numLinesToSkip

    number of lines to skip, default=1

    delimiter

    delimiter, default=','. Other options:

    '\t': for tab-delimitd
    CSVRecordReader.QUOTE_HANDLING_DELIMITER: for records containing quotes with commas in them

    quote

    quote, default='\"'

    batchSize

    batch size, default=128

    classification

    whether for classification, default=false

    labelIndex

    label index when classification=true, default=0

    numPossibleLabels

    label cardinality when classification=true, default=2

    regression

    whether for regression, default=false

    labelIndexTo

    only for regression, the last index (inclusive) for multi-output regression, default=0

    returns

    dataset iterator

12. def fromPlainCSVWithSchemaToSRR(filePath: String, columnNameTypes: Array[(String, String)], columnCategoricalValues: Map[String, Array[String]] = Map(), removeColumns: Array[String] = Array(), categorical2OneHots: Array[String] = Array(), categorical2Ints: Array[String] = Array(), numLinesToSkip: Int = 1, delimiter: Char = CSVRecordReader.DEFAULT_DELIMITER, quote: Char = CSVRecordReader.DEFAULT_QUOTE, batchSize: Int = 128, classification: Boolean = false, labelIndex: Int = 0, numPossibleLabels: Int = 2, regression: Boolean = false, labelIndexTo: Int = 0, seed: Long = 2018L): (RecordReaderDataSetIterator, Schema, RecordReader)

    

13. def fromSeqCSVs(baseDir: String, labelIndex: Int, numClasses: Int, regression: Boolean = false, numLinesToSkip: Int = 1, delimiter: String = ",", batchSize: Int = 128, seed: Long = 2018L): SequenceRecordReaderDataSetIterator

    

    Load CSV files, one file per sequence, within one file, one row per time step, with columnar features and label index)

    Load CSV files, one file per sequence, within one file, one row per time step, with columnar features and label index)

    baseDir

    folder

    labelIndex

    label index

    numClasses

    number of classes

    regression

    whether for regression, default=false (for classification)

    numLinesToSkip

    number of lines to skip, default=1

    delimiter

    delimiter, default=','

    batchSize

    batch size, default=128

    seed

    seed for random generator, default=2018L

14. final def getClass(): Class[_]

    

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15. def hashCode(): Int

    

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16. final def isInstanceOf[T0]: Boolean

    

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18. final def notify(): Unit

    

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20. final def synchronized[T0](arg0: ⇒ T0): T0

    

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21. def toString(): String

    

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22. final def wait(): Unit

    

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23. final def wait(arg0: Long, arg1: Int): Unit

    

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