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object DatasetUtils

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  1. case class CardinalityTriplet[T](groupCounts: List[Int], currentValue: T, currentCount: Int) extends Product with Serializable

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  1. final def !=(arg0: Any): Boolean
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  2. final def ##(): Int
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    @throws( ... ) @native()
  6. def countCardinality[T](input: Seq[T]): Array[Int]
  7. final def eq(arg0: AnyRef): Boolean
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  8. def equals(arg0: Any): Boolean
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  9. def finalize(): Unit
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  10. final def getClass(): Class[_]
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  11. def getInitScores(rows: Array[Row], initScoreColumn: Option[String], schema: StructType): Option[Array[Double]]
  12. def getRowAsDoubleArray(row: Row, columnParams: ColumnParams): Array[Double]
  13. def hashCode(): Int
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  17. final def notifyAll(): Unit
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  18. def releaseArrays(labelsChunkedArray: floatChunkedArray, weightChunkedArrayOpt: Option[floatChunkedArray], initScoreChunkedArrayOpt: Option[doubleChunkedArray]): Unit
  19. def sampleRowsForArrayType(rowsIter: Iterator[Row], columnParams: ColumnParams): (Iterator[Row], Boolean)

    Sample the first several rows to determine whether to construct sparse or dense matrix in lightgbm native code.

    Sample the first several rows to determine whether to construct sparse or dense matrix in lightgbm native code.

    rowsIter

    Iterator of rows.

    columnParams

    The column parameters.

    returns

    A reconstructed iterator with the same original rows and whether the matrix should be sparse or dense.

  20. final def synchronized[T0](arg0: ⇒ T0): T0
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  21. def toString(): String
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  22. def validateGroupColumn(col: String, schema: StructType): Unit
  23. final def wait(): Unit
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  24. final def wait(arg0: Long, arg1: Int): Unit
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  25. final def wait(arg0: Long): Unit
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