Package weka.core.neighboursearch.kdtrees

Class KDTreeNodeSplitter

    • Field Summary

      Fields 
      Modifier and Type Field Description
      static int MAX
      Index of max value in an array of attributes' range.
      static int MIN
      Index of min value in an array of attributes' range.
      static int WIDTH
      Index of width value (max-min) in an array of attributes' range.

    • Method Summary

      All Methods Instance Methods Abstract Methods Concrete Methods 
      Modifier and Type Method Description
      java.lang.String[] getOptions()
      Gets the current settings of the object.
      java.lang.String getRevision()
      Returns the revision string.
      java.util.Enumeration listOptions()
      Returns an enumeration describing the available options.
      void setEuclideanDistanceFunction​(EuclideanDistance func)
      Sets the EuclideanDistance object to use for splitting nodes.
      void setInstanceList​(int[] instList)
      Sets the master index array containing indices of the training instances.
      void setInstances​(Instances inst)
      Sets the training instances on which the tree is (or is to be) built.
      void setNodeWidthNormalization​(boolean normalize)
      Sets whether if a nodes region is normalized or not.
      void setOptions​(java.lang.String[] options)
      Parses a given list of options.
      abstract void splitNode​(KDTreeNode node, int numNodesCreated, double[][] nodeRanges, double[][] universe)
      Splits a node into two.

      • Methods inherited from class java.lang.Object

        equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

    • Field Detail

      • MIN

        public static final int MIN
        Index of min value in an array of attributes' range.
        See Also:
        Constant Field Values

      • MAX

        public static final int MAX
        Index of max value in an array of attributes' range.
        See Also:
        Constant Field Values

      • WIDTH

        public static final int WIDTH
        Index of width value (max-min) in an array of attributes' range.
        See Also:
        Constant Field Values

    • Constructor Detail

      • KDTreeNodeSplitter

        public KDTreeNodeSplitter()
        default constructor.

      • KDTreeNodeSplitter

        public KDTreeNodeSplitter​(int[] instList,
                          Instances insts,
                          EuclideanDistance e)
        Creates a new instance of KDTreeNodeSplitter.
        Parameters:
        instList - Reference of the master index array.
        insts - The set of training instances on which the tree is built.
        e - The EuclideanDistance object that is used in tree contruction.

    • Method Detail

      • listOptions

        public java.util.Enumeration listOptions()
        Returns an enumeration describing the available options.
        Specified by:
        listOptions in interface OptionHandler
        Returns:
        an enumeration of all the available options.

      • setOptions

        public void setOptions​(java.lang.String[] options)
                throws java.lang.Exception
        Parses a given list of options.
        Specified by:
        setOptions in interface OptionHandler
        Parameters:
        options - the list of options as an array of strings
        Throws:
        java.lang.Exception - if an option is not supported

      • getOptions

        public java.lang.String[] getOptions()
        Gets the current settings of the object.
        Specified by:
        getOptions in interface OptionHandler
        Returns:
        an array of strings suitable for passing to setOptions

      • splitNode

        public abstract void splitNode​(KDTreeNode node,
                               int numNodesCreated,
                               double[][] nodeRanges,
                               double[][] universe)
                        throws java.lang.Exception
        Splits a node into two. After splitting two new nodes are created and correctly initialised. And, node.left and node.right are set appropriately.
        Parameters:
        node - The node to split.
        numNodesCreated - The number of nodes that so far have been created for the tree, so that the newly created nodes are assigned correct/meaningful node numbers/ids.
        nodeRanges - The attributes' range for the points inside the node that is to be split.
        universe - The attributes' range for the whole point-space.
        Throws:
        java.lang.Exception - If there is some problem in splitting the given node.

      • setInstances

        public void setInstances​(Instances inst)
        Sets the training instances on which the tree is (or is to be) built.
        Parameters:
        inst - The training instances.

      • setInstanceList

        public void setInstanceList​(int[] instList)
        Sets the master index array containing indices of the training instances. This array will be rearranged as the tree is built, so that each node is assigned a portion in this array which contain the instances insides the node's region.
        Parameters:
        instList - The master index array.

      • setEuclideanDistanceFunction

        public void setEuclideanDistanceFunction​(EuclideanDistance func)
        Sets the EuclideanDistance object to use for splitting nodes.
        Parameters:
        func - The EuclideanDistance object.

      • setNodeWidthNormalization

        public void setNodeWidthNormalization​(boolean normalize)
        Sets whether if a nodes region is normalized or not. If set to true then, when selecting the widest attribute/dimension for splitting, the width of each attribute/dimension, of the points inside the node's region, is divided by the width of that attribute/dimension for the whole point-space. Thus, each attribute/dimension of that node is normalized.
        Parameters:
        normalize - Should be true if normalization is required.

      • getRevision

        public java.lang.String getRevision()
        Returns the revision string.
        Specified by:
        getRevision in interface RevisionHandler
        Returns:
        the revision