Interface SGDVector

All Superinterfaces:
Iterable<VectorTuple>, Serializable, Tensor
All Known Implementing Classes:
DenseVector, ShrinkingVector, SparseVector
public interface SGDVector extends Tensor, Iterable<VectorTuple>
Interface for 1 dimensional Tensors.

Vectors have immutable sizes and immutable indices (so SparseVector can't grow).

  • Method Details

    • copy

      SGDVector copy()
      Returns a deep copy of this vector.
      Returns:
      A copy of this vector.

    • size

      int size()
      Returns the dimensionality of this vector.
      Returns:
      The dimensionality of the vector.

    • numActiveElements

      int numActiveElements()
      Returns the number of non-zero elements (on construction, an element could be set to zero and it would still remain active).
      Returns:
      The number of non-zero elements.

    • scale

      SGDVector scale(double coefficient)
      Generates a new vector with each element scaled by coefficient.
      Parameters:
      coefficient - The coefficient to scale the elements by.
      Returns:
      A new SGDVector.

    • add

      void add(int index, double value)
      Adds value to the element at index.
      Parameters:
      index - The index to update.
      value - The value to add.

    • add

      SGDVector add(SGDVector other)
      Adds other to this vector, producing a new SGDVector. Adding Dense to Dense/Sparse produces a DenseVector, adding Sparse to Sparse produces a SparseVector.
      Parameters:
      other - The vector to add.
      Returns:
      A new SGDVector where each element value = this.get(i) + other.get(i).

    • subtract

      SGDVector subtract(SGDVector other)
      Subtracts other from this vector, producing a new SGDVector. Subtracting Dense from Dense/Sparse produces a DenseVector, subtracting Sparse from Sparse produces a SparseVector.
      Parameters:
      other - The vector to subtract.
      Returns:
      A new SGDVector where each element value = this.get(i) - other.get(i).

    • dot

      double dot(SGDVector other)
      Calculates the dot product between this vector and other.
      Parameters:
      other - The other vector.
      Returns:
      The dot product.

    • outer

      Matrix outer(SGDVector other)
      Generates the matrix representing the outer product between the two vectors.
      Parameters:
      other - Another SGDVector
      Returns:
      The outer product Matrix.

    • sum

      double sum()
      Calculates the sum of this vector.
      Returns:
      The sum.

    • twoNorm

      double twoNorm()
      Calculates the euclidean norm for this vector.
      Specified by:
      twoNorm in interface Tensor
      Returns:
      The euclidean norm.

    • oneNorm

      double oneNorm()
      Calculates the Manhattan norm for this vector.
      Returns:
      The Manhattan norm.

    • get

      double get(int index)
      Gets an element from this vector.
      Parameters:
      index - The index of the element.
      Returns:
      The value at that index.

    • set

      void set(int index, double value)
      Sets the index to the value.
      Parameters:
      index - The index to set.
      value - The value to set it to.

    • indexOfMax

      int indexOfMax()
      Returns the index of the maximum value. Requires probing the array.
      Returns:
      The index of the maximum value.

    • maxValue

      double maxValue()
      Returns the maximum value. Requires probing the array.
      Returns:
      The maximum value.

    • minValue

      double minValue()
      Returns the minimum value. Requires probing the array.
      Returns:
      The minimum value.

    • normalize

      void normalize(VectorNormalizer normalizer)
      Normalizes the vector using the supplied vector normalizer.
      Parameters:
      normalizer - The kind of normalization to apply.

    • l2Distance

      default double l2Distance(SGDVector other)
      Synonym for euclideanDistance.
      Parameters:
      other - The other vector.
      Returns:
      The l2 norm of the difference between the two vectors.

    • euclideanDistance

      double euclideanDistance(SGDVector other)
      The l2 or euclidean distance between this vector and the other vector.
      Parameters:
      other - The other vector.
      Returns:
      The euclidean distance between them.

    • l1Distance

      double l1Distance(SGDVector other)
      The l1 or Manhattan distance between this vector and the other vector.
      Parameters:
      other - The other vector.
      Returns:
      The l1 distance.

    • cosineDistance

      default double cosineDistance(SGDVector other)
      Calculates the cosine distance of two vectors. 1 - cos(x,y)
      Parameters:
      other - The other vector.
      Returns:
      1 - cosine similarity (this,other)

    • cosineSimilarity

      default double cosineSimilarity(SGDVector other)
      Calculates the cosine similarity of two vectors. cos(x,y) = dot(x,y) / (norm(x) * norm(y))
      Parameters:
      other - The other vector.
      Returns:
      cosine similarity (this,other)

    • variance

      default double variance()
      Calculates the variance of this vector.
      Returns:
      The variance of the vector.

    • variance

      double variance(double mean)
      Calculates the variance of this vector based on the supplied mean.
      Parameters:
      mean - The mean of the vector.
      Returns:
      The variance of the vector.