Record Class Bag

java.lang.Object
java.lang.Record
smile.validation.Bag
Record Components:
samples - the random samples.
oob - the out of bag samples.
All Implemented Interfaces:
Serializable

public record Bag(int[] samples, int[] oob) extends Record implements Serializable
A bag of random selected samples.
See Also:
  • Constructor Summary

    Constructors
    Constructor
    Description
    Bag(int[] samples, int[] oob)
    Creates an instance of a Bag record class.
  • Method Summary

    Modifier and Type
    Method
    Description
    final boolean
    Indicates whether some other object is "equal to" this one.
    final int
    Returns a hash code value for this object.
    int[]
    oob()
    Returns the value of the oob record component.
    int[]
    Returns the value of the samples record component.
    static Bag
    split(int n, double holdout)
    Splits samples into random train and test subsets.
    split(DataFrame data, double holdout)
    Splits a data frame into random train and test subsets.
    stratify(DataFrame data, String category, double holdout)
    Stratified splitting a data frame into random train and test subsets.
    final String
    Returns a string representation of this record class.

    Methods inherited from class Object

    clone, finalize, getClass, notify, notifyAll, wait, wait, wait
  • Constructor Details

    • Bag

      public Bag(int[] samples, int[] oob)
      Creates an instance of a Bag record class.
      Parameters:
      samples - the value for the samples record component
      oob - the value for the oob record component
  • Method Details

    • split

      public static Bag split(int n, double holdout)
      Splits samples into random train and test subsets.
      Parameters:
      n - the number of samples.
      holdout - the proportion of samples in the test split.
      Returns:
      the sample split.
    • split

      public static Tuple2<DataFrame, DataFrame> split(DataFrame data, double holdout)
      Splits a data frame into random train and test subsets.
      Parameters:
      data - the data frame.
      holdout - the proportion of samples in the test split.
      Returns:
      the data splits.
    • stratify

      public static Tuple2<DataFrame, DataFrame> stratify(DataFrame data, String category, double holdout)
      Stratified splitting a data frame into random train and test subsets.
      Parameters:
      data - the data frame.
      category - the column as the strata label.
      holdout - the proportion of samples in the test split.
      Returns:
      the data splits.
    • toString

      public final String toString()
      Returns a string representation of this record class. The representation contains the name of the class, followed by the name and value of each of the record components.
      Specified by:
      toString in class Record
      Returns:
      a string representation of this object
    • hashCode

      public final int hashCode()
      Returns a hash code value for this object. The value is derived from the hash code of each of the record components.
      Specified by:
      hashCode in class Record
      Returns:
      a hash code value for this object
    • equals

      public final boolean equals(Object o)
      Indicates whether some other object is "equal to" this one. The objects are equal if the other object is of the same class and if all the record components are equal. All components in this record class are compared with Objects::equals(Object,Object).
      Specified by:
      equals in class Record
      Parameters:
      o - the object with which to compare
      Returns:
      true if this object is the same as the o argument; false otherwise.
    • samples

      public int[] samples()
      Returns the value of the samples record component.
      Returns:
      the value of the samples record component
    • oob

      public int[] oob()
      Returns the value of the oob record component.
      Returns:
      the value of the oob record component