Class PearsonCorrelationDistance

  • All Implemented Interfaces:
    Distance<NumberVector>, NumberVectorDistance<NumberVector>, PrimitiveDistance<NumberVector>

    public class PearsonCorrelationDistance
    extends AbstractNumberVectorDistance
    Pearson correlation distance function for feature vectors. The Pearson correlation distance is computed from the Pearson correlation coefficient r as: 1-r. Hence, possible values of this distance are between 0 and 2. The distance between two vectors will be low (near 0), if their attribute values are dimension-wise strictly positively correlated, it will be high (near 2), if their attribute values are dimension-wise strictly negatively correlated. For Features with uncorrelated attributes, the distance value will be intermediate (around 1).
    Since:
    0.3
    Author:
    Arthur Zimek
    • Constructor Detail

      • PearsonCorrelationDistance

        @Deprecated
        public PearsonCorrelationDistance()
        Deprecated.
        Use static instance!
        Constructor - use STATIC instead.
    • Method Detail

      • distance

        public double distance​(NumberVector v1,
                               NumberVector v2)
        Computes the Pearson correlation distance for two given feature vectors. The Pearson correlation distance is computed from the Pearson correlation coefficient r as: 1-r. Hence, possible values of this distance are between 0 and 2.
        Parameters:
        v1 - first feature vector
        v2 - second feature vector
        Returns:
        the Pearson correlation distance for two given feature vectors v1 and v2
      • toString

        public java.lang.String toString()
        Overrides:
        toString in class java.lang.Object
      • equals

        public boolean equals​(java.lang.Object obj)
        Overrides:
        equals in class java.lang.Object
      • hashCode

        public int hashCode()
        Overrides:
        hashCode in class java.lang.Object