Class LinearNNSearch

  • All Implemented Interfaces:
    Serializable

    public class LinearNNSearch
    extends NearestNeighbourSearch
    Class implementing the brute force search algorithm for nearest neighbour search.

    Valid options are:

     -S
      Skip identical instances (distances equal to zero).
     
    Version:
    $Revision: 8034 $
    Author:
    Ashraf M. Kibriya (amk14[at-the-rate]cs[dot]waikato[dot]ac[dot]nz)
    See Also:
    Serialized Form
    • Field Detail

      • m_Distances

        protected double[] m_Distances
        Array holding the distances of the nearest neighbours. It is filled up both by nearestNeighbour() and kNearestNeighbours().
      • m_SkipIdentical

        protected boolean m_SkipIdentical
        Whether to skip instances from the neighbours that are identical to the query instance.
    • Constructor Detail

      • LinearNNSearch

        public LinearNNSearch()
        Constructor. Needs setInstances(Instances) to be called before the class is usable.
      • LinearNNSearch

        public LinearNNSearch​(Instances insts)
        Constructor that uses the supplied set of instances.
        Parameters:
        insts - the instances to use
    • Method Detail

      • globalInfo

        public String globalInfo()
        Returns a string describing this nearest neighbour search algorithm.
        Overrides:
        globalInfo in class NearestNeighbourSearch
        Returns:
        a description of the algorithm for displaying in the explorer/experimenter gui
      • skipIdenticalTipText

        public String skipIdenticalTipText()
        Returns the tip text for this property.
        Returns:
        tip text for this property suitable for displaying in the explorer/experimenter gui
      • setSkipIdentical

        public void setSkipIdentical​(boolean skip)
        Sets the property to skip identical instances (with distance zero from the target) from the set of neighbours returned.
        Parameters:
        skip - if true, identical intances are skipped
      • getSkipIdentical

        public boolean getSkipIdentical()
        Gets whether if identical instances are skipped from the neighbourhood.
        Returns:
        true if identical instances are skipped
      • nearestNeighbour

        public Instance nearestNeighbour​(Instance target)
                                  throws Exception
        Returns the nearest instance in the current neighbourhood to the supplied instance.
        Specified by:
        nearestNeighbour in class NearestNeighbourSearch
        Parameters:
        target - The instance to find the nearest neighbour for.
        Returns:
        the nearest instance
        Throws:
        Exception - if the nearest neighbour could not be found.
      • kNearestNeighbours

        public Instances kNearestNeighbours​(Instance target,
                                            int kNN)
                                     throws Exception
        Returns k nearest instances in the current neighbourhood to the supplied instance.
        Specified by:
        kNearestNeighbours in class NearestNeighbourSearch
        Parameters:
        target - The instance to find the k nearest neighbours for.
        kNN - The number of nearest neighbours to find.
        Returns:
        the k nearest neighbors
        Throws:
        Exception - if the neighbours could not be found.
      • getDistances

        public double[] getDistances()
                              throws Exception
        Returns the distances of the k nearest neighbours. The kNearestNeighbours or nearestNeighbour must always be called before calling this function. If this function is called before calling either the kNearestNeighbours or the nearestNeighbour, then it throws an exception. If, however, if either of the nearestNeighbour functions are called at any point in the past then no exception is thrown and the distances of the training set from the last supplied target instance (to either one of the nearestNeighbour functions) is/are returned.
        Specified by:
        getDistances in class NearestNeighbourSearch
        Returns:
        array containing the distances of the nearestNeighbours. The length and ordering of the array is the same as that of the instances returned by nearestNeighbour functions.
        Throws:
        Exception - if called before calling kNearestNeighbours or nearestNeighbours.
      • setInstances

        public void setInstances​(Instances insts)
                          throws Exception
        Sets the instances comprising the current neighbourhood.
        Overrides:
        setInstances in class NearestNeighbourSearch
        Parameters:
        insts - The set of instances on which the nearest neighbour search is carried out. Usually this set is the training set.
        Throws:
        Exception - if setting of instances fails
      • update

        public void update​(Instance ins)
                    throws Exception
        Updates the LinearNNSearch to cater for the new added instance. This implementation only updates the ranges of the DistanceFunction class, since our set of instances is passed by reference and should already have the newly added instance.
        Specified by:
        update in class NearestNeighbourSearch
        Parameters:
        ins - The instance to add. Usually this is the instance that is added to our neighbourhood i.e. the training instances.
        Throws:
        Exception - if the given instances are null
      • addInstanceInfo

        public void addInstanceInfo​(Instance ins)
        Adds the given instance info. This implementation updates the range datastructures of the DistanceFunction class.
        Overrides:
        addInstanceInfo in class NearestNeighbourSearch
        Parameters:
        ins - The instance to add the information of. Usually this is the test instance supplied to update the range of attributes in the distance function.