Package org.processmining.plugins.workshop.Yaguang.WekaDiscriminationTree

Class ClassifierTree

    • Field Detail

      • m_toSelectModel

        protected ModelSelection m_toSelectModel
        The model selection method.

      • m_isLeaf

        protected boolean m_isLeaf
        True if node is leaf.

      • m_isEmpty

        protected boolean m_isEmpty
        True if node is empty.

      • m_isDifferent

        protected boolean m_isDifferent

      • m_train

        protected Instances m_train
        The training instances.

      • m_test

        protected Distribution m_test
        The pruning instances.

      • m_id

        protected int m_id
        The id for the node.

      • m_isChanged

        protected boolean m_isChanged
        indicate of the node is changed.

    • Constructor Detail

      • ClassifierTree

        public ClassifierTree​(ModelSelection toSelectLocModel)
        Constructor.

    • Method Detail

      • nextID

        protected static long nextID()
        Gets the next unique node ID.
        Returns:
        the next unique node ID.

      • doRemoveUselessNodes

        public java.util.Map<java.lang.Double,​java.lang.Double[]> doRemoveUselessNodes​(java.util.Map<java.lang.Double,​java.lang.Double[]> info,
                                                                                     java.lang.Double[][] discriminationInfo)

      • pickMaxIdx

        public int pickMaxIdx​(double[][] info)

      • doChangeLeafLabels

        public void doChangeLeafLabels​(java.util.Set<java.lang.Integer> nodeIdsToRelabel)

      • doRelabel

        public void doRelabel​(java.util.Map<java.lang.Double,​java.lang.Double[]> info,
                      java.lang.Double[][] discriminationInfo,
                      int NDCtoDC)

      • resetID

        protected static void resetID()
        Resets the unique node ID counter (e.g. between repeated separate print types)

      • doDistributionForInstance

        public final double[][] doDistributionForInstance​(Instance instance,
                                                  boolean useLaplace)
                                           throws java.lang.Exception
        Throws:
        java.lang.Exception

      • buildClassifier

        public void buildClassifier​(Instances data)
                     throws java.lang.Exception
        Method for building a classifier tree.
        Throws:
        java.lang.Exception - if something goes wrong

      • buildTree

        public void buildTree​(Instances data,
                      boolean keepData)
               throws java.lang.Exception
        Builds the tree structure.
        Parameters:
        data - the data for which the tree structure is to be generated.
        keepData - is training data to be kept?
        Throws:
        java.lang.Exception - if something goes wrong

      • buildTree

        public void buildTree​(Instances train,
                      Instances test,
                      boolean keepData)
               throws java.lang.Exception
        Builds the tree structure with hold out set
        Parameters:
        train - the data for which the tree structure is to be generated.
        test - the test data for potential pruning
        keepData - is training Data to be kept?
        Throws:
        java.lang.Exception - if something goes wrong

      • classifyInstance

        public double classifyInstance​(Instance instance)
                        throws java.lang.Exception
        Classifies an instance.
        Throws:
        java.lang.Exception - if something goes wrong

      • cleanup

        public final void cleanup​(Instances justHeaderInfo)
        Cleanup in order to save memory.

      • distributionForInstance

        public final double[] distributionForInstance​(Instance instance,
                                              boolean useLaplace)
                                       throws java.lang.Exception
        Returns class probabilities for a weighted instance.
        Throws:
        java.lang.Exception - if something goes wrong

      • assignIDs

        public int assignIDs​(int lastID)
        Assigns a uniqe id to every node in the tree.

      • isLeaf

        public boolean isLeaf()

      • graphType

        public int graphType()
        Returns the type of graph this classifier represents.
        Specified by:
        graphType in interface Drawable
        Returns:
        Drawable.TREE

      • graph

        public java.lang.String graph()
                       throws java.lang.Exception
        Returns graph describing the tree.
        Specified by:
        graph in interface Drawable
        Returns:
        the graph described by a string
        Throws:
        java.lang.Exception - if something goes wrong

      • prefix

        public java.lang.String prefix()
                        throws java.lang.Exception
        Returns tree in prefix order.
        Throws:
        java.lang.Exception - if something goes wrong

      • getLabel

        public java.lang.String getLabel()
                          throws java.lang.Exception
        Throws:
        java.lang.Exception

      • setIsDifferent

        public void setIsDifferent​(boolean isDifferent)

      • toSource

        public java.lang.StringBuffer[] toSource​(java.lang.String className)
                                  throws java.lang.Exception
        Returns source code for the tree as an if-then statement. The class is assigned to variable "p", and assumes the tested instance is named "i". The results are returned as two stringbuffers: a section of code for assignment of the class, and a section of code containing support code (eg: other support methods).
        Parameters:
        className - the classname that this static classifier has
        Returns:
        an array containing two stringbuffers, the first string containing assignment code, and the second containing source for support code.
        Throws:
        java.lang.Exception - if something goes wrong

      • numLeaves

        public int numLeaves()
        Returns number of leaves in tree structure.

      • numNodes

        public int numNodes()
        Returns number of nodes in tree structure.

      • toString

        public java.lang.String toString()
        Prints tree structure.
        Overrides:
        toString in class java.lang.Object

      • getNewTree

        protected ClassifierTree getNewTree​(Instances data)
                             throws java.lang.Exception
        Returns a newly created tree.
        Parameters:
        data - the training data
        Throws:
        java.lang.Exception - if something goes wrong

      • getNewTree

        protected ClassifierTree getNewTree​(Instances train,
                                    Instances test)
                             throws java.lang.Exception
        Returns a newly created tree.
        Parameters:
        data - the training data
        test - the pruning data.
        Throws:
        java.lang.Exception - if something goes wrong

      • color

        public void color​(ClassifierTree m_root)
           throws java.lang.Exception
        Set m_isDifferent to true for those leafs of the classifireTree whose label are dofferent with the corresponding leaf in the input classifireTree
        Throws:
        java.lang.Exception