Uses of Class
org.knime.base.node.mine.sota.logic.SotaTreeCell

Packages that use SotaTreeCell
org.knime.base.node.mine.sota Contains the Sota node, which can be used for clustering hirarchically numerical and fuzzy data and visualize the resulting cluster tree. 
org.knime.base.node.mine.sota.distances Contains classes to compute distances for SOTA. 
org.knime.base.node.mine.sota.logic Contains the logic classes of SOTA. 
org.knime.base.node.mine.sota.predictor Contains the Sotapredictor node, which can be used for class prediction of incoming data. 
org.knime.base.node.mine.sota.view Contains the view classes of the Sota node. 
 

Uses of SotaTreeCell in org.knime.base.node.mine.sota
 

Methods in org.knime.base.node.mine.sota that return SotaTreeCell
 SotaTreeCell SotaPortObject.getSotaRoot()
           
 

Uses of SotaTreeCell in org.knime.base.node.mine.sota.distances
 

Methods in org.knime.base.node.mine.sota.distances with parameters of type SotaTreeCell
static double Distances.getCorrelationDistance(DataRow row, SotaTreeCell cell, double offset, boolean abs, boolean fuzzy)
          Returns the coefficient of correlation distance between the cells values and the number cells of the given row with a given offset.
static double Distances.getCosinusDistance(DataRow row, SotaTreeCell cell, double offset, boolean fuzzy)
          Returns the cosinus distance between the cells values and the number cells of the given row with a given offset.
 double EuclideanDistanceManager.getDistance(DataRow row, SotaTreeCell cell)
          Returns the distance between the given cell and row.
 double ManhattanDistanceManager.getDistance(DataRow row, SotaTreeCell cell)
          Returns the distance between the given cell and row.
 double DistanceManager.getDistance(DataRow row, SotaTreeCell cell)
          Returns the distance between the given cell and row.
 double CosinusDistanceManager.getDistance(DataRow row, SotaTreeCell cell)
          Returns the distance between the given cell and row.
static double Distances.getEuclideanDistance(DataRow row, SotaTreeCell cell, boolean fuzzy)
          Returns the euclidean distance between a given DataRow and SotaTreeCell using the Minkowski distance with power 2.
static double Distances.getManhattanDistance(DataRow row, SotaTreeCell cell, boolean fuzzy)
          Returns the manhattan distance between a given DataRow and SotaTreeCell using the Minkowski distance with power 1.
static double Distances.getMean(SotaTreeCell cell)
          Returns the mean value of the given cell.
static double Distances.getMinkowskiDistance(int power, DataRow row, SotaTreeCell cell, boolean fuzzy)
          Calculates the Minkowski distance between a regular DataRow and a SotaTreeCell.
static double Distances.getStandardDeviation(SotaTreeCell cell)
          Returns the standard deviation of the given cell.
 

Uses of SotaTreeCell in org.knime.base.node.mine.sota.logic
 

Methods in org.knime.base.node.mine.sota.logic that return SotaTreeCell
 SotaTreeCell SotaTreeCellFactory.createCell()
          Creates new instance of Cell with the factorys dimension and returns it.
 SotaTreeCell SotaTreeCellFactory.createCell(double[] minSupp, double[] minCore, double[] maxCore, double[] maxSupp, int level)
          Creates new insatnce of Cell with given min, max Core and Support data and level and returns it.
 SotaTreeCell SotaTreeCellFactory.createCell(double[] data, int level)
          Creates new instance of Cell with given data and level and returns it.
 SotaTreeCell SotaTreeCellFactory.createCell(FuzzyIntervalValue[] data, int level)
          Creates new insatnce of Cell with given FuzzyIntervalValue data and level and returns it.
 SotaTreeCell SotaTreeCellFactory.createCell(int level)
          Creates new instance of Cell with the factorys dimension and the given level and returns it.
 SotaTreeCell SotaTreeCellFactory.createCell(SotaCell[] data, int level)
          Creates new instance of Cell with given data and level and returns it.
 SotaTreeCell SotaTreeCellFactory.createNode()
          Creates new instance of Cell with the factorys dimension and returns it.
 SotaTreeCell SotaTreeCellFactory.createNode(int level)
          Creates new instance of Cell with the factorys dimension and given level and returns it.
 SotaTreeCell SotaTreeCellFactory.createNode(SotaCell[] data, int level)
          Creates new instance of Cell with given data and level and returns it.
 SotaTreeCell SotaTreeCell.getAncestor()
          Returns the cells ancestor.
 SotaTreeCell SotaTreeCell.getLeft()
          Returns the left child Cell of the current Node, or null.
 SotaTreeCell SotaTreeCell.getRight()
          Returns the cells (Nodes) right child Cell.
 SotaTreeCell SotaManager.getRoot()
           
 SotaTreeCell SotaTreeCell.getSister()
           
abstract  SotaTreeCell SotaHelper.initializeTree()
          Initializes the Sota tree with specific SotaCells like SotaFuzzyCell or SotaDoubleCell.
 SotaTreeCell SotaFuzzyHelper.initializeTree()
          Initializes the Sota tree with specific SotaCells like SotaFuzzyCell or SotaDoubleCell.
 SotaTreeCell SotaNumberHelper.initializeTree()
          Initializes the Sota tree with specific SotaCells like SotaFuzzyCell or SotaDoubleCell.
 

Methods in org.knime.base.node.mine.sota.logic with parameters of type SotaTreeCell
abstract  void SotaHelper.adjustSotaCell(SotaTreeCell cell, DataRow row, double learningrate, String cellClass)
          Adjusts the given SotaTreeCell related to the given DataRow and learningrate and assigns the given class.
 void SotaFuzzyHelper.adjustSotaCell(SotaTreeCell cell, DataRow row, double learningrate, String cellClass)
          Adjusts the given SotaTreeCell related to the given DataRow and learningrate and assigns the given class.
 void SotaNumberHelper.adjustSotaCell(SotaTreeCell cell, DataRow row, double learningrate, String cellClass)
          Adjusts the given SotaTreeCell related to the given DataRow and learningrate and assigns the given class.
static void SotaManager.getCells(ArrayList<SotaTreeCell> cells, SotaTreeCell currentCell)
          Collects all cells of the tree recursive.
 void SotaTreeCell.loadFrom(ModelContentRO modelContent, int index, SotaTreeCell anchestor, boolean isLeft)
          Loads the values from the given ModelContentWO.
 void SotaTreeCell.setAncestor(SotaTreeCell anc)
          Sets the given ancestor value.
 void SotaTreeCell.setLeft(SotaTreeCell l)
          Sets the cells (Nodes) left child Cell.
 void SotaTreeCell.setRight(SotaTreeCell r)
          Sets the given Cell as the cells right child Cell.
 void SotaManager.setRoot(SotaTreeCell root)
          Sets the root node.
 void SotaTreeCell.setSister(SotaTreeCell sister)
           
 

Method parameters in org.knime.base.node.mine.sota.logic with type arguments of type SotaTreeCell
static void SotaManager.getCells(ArrayList<SotaTreeCell> cells, SotaTreeCell currentCell)
          Collects all cells of the tree recursive.
 

Uses of SotaTreeCell in org.knime.base.node.mine.sota.predictor
 

Constructors in org.knime.base.node.mine.sota.predictor with parameters of type SotaTreeCell
SotaPredictorCellFactory(SotaTreeCell root, int[] indicesOfIncludedColumns, String distance)
          Creates new instance of SotaPredictorCellFactory with given SotaManager, array of indices of columns to use for prediction and the distance metric to use.
 

Uses of SotaTreeCell in org.knime.base.node.mine.sota.view
 

Methods in org.knime.base.node.mine.sota.view that return SotaTreeCell
 SotaTreeCell SotaDrawingPane.getRoot()
           
 

Methods in org.knime.base.node.mine.sota.view with parameters of type SotaTreeCell
 void SotaDrawingPane.setRoot(SotaTreeCell root)
           
 

Constructors in org.knime.base.node.mine.sota.view with parameters of type SotaTreeCell
SotaDrawingPane(SotaTreeCell root, DataArray data, DataArray originalData, boolean isHFuzzyData, int maxHLevel)
          Creates new instance of SotaDrawingPane, which draws the given data and the trained binary cluster tree given by its root node.
 



Copyright, 2003 - 2010. All rights reserved.
University of Konstanz, Germany.
Chair for Bioinformatics and Information Mining, Prof. Dr. Michael R. Berthold.
You may not modify, publish, transmit, transfer or sell, reproduce, create derivative works from, distribute, perform, display, or in any way exploit any of the content, in whole or in part, except as otherwise expressly permitted in writing by the copyright owner or as specified in the license file distributed with this product.