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The Waikato Environment for Knowledge Analysis (WEKA), a machine
learning workbench. This is the stable version. Apart from bugfixes, this version
does not receive any other updates.
/*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see .
*/
/*
* Tester.java
* Copyright (C) 2005-2012 University of Waikato, Hamilton, New Zealand
*
*/
package weka.experiment;
import java.io.Serializable;
import weka.core.Instance;
import weka.core.Instances;
import weka.core.Range;
/**
* Interface for different kinds of Testers in the Experimenter.
*
* @author FracPete (fracpete at waikato dot ac dot nz)
* @version $Revision: 8034 $
*/
public interface Tester
extends Serializable {
/**
* returns the name of the testing algorithm
*/
public String getDisplayName();
/**
* returns a string that is displayed as tooltip on the "perform test"
* button in the experimenter
*/
public String getToolTipText();
/**
* retrieves all the settings from the given Tester
*
* @param tester the Tester to get the settings from
*/
public void assign(Tester tester);
/**
* Sets the matrix to use to produce the output.
* @param matrix the instance to use to produce the output
* @see ResultMatrix
*/
public void setResultMatrix(ResultMatrix matrix);
/**
* Gets the instance that produces the output.
* @return the instance to produce the output
*/
public ResultMatrix getResultMatrix();
/**
* Set whether standard deviations are displayed or not.
* @param s true if standard deviations are to be displayed
*/
public void setShowStdDevs(boolean s);
/**
* Returns true if standard deviations have been requested.
* @return true if standard deviations are to be displayed.
*/
public boolean getShowStdDevs();
/**
* Gets the number of datasets in the resultsets
*
* @return the number of datasets in the resultsets
*/
public int getNumDatasets();
/**
* Gets the number of resultsets in the data.
*
* @return the number of resultsets in the data
*/
public int getNumResultsets();
/**
* Gets a string descriptive of the specified resultset.
*
* @param index the index of the resultset
* @return a descriptive string for the resultset
*/
public String getResultsetName(int index);
/**
* Checks whether the resultset with the given index shall be displayed.
*
* @param index the index of the resultset to check whether it shall be displayed
* @return whether the specified resultset is displayed
*/
public boolean displayResultset(int index);
/**
* Computes a paired t-test comparison for a specified dataset between
* two resultsets.
*
* @param datasetSpecifier the dataset specifier
* @param resultset1Index the index of the first resultset
* @param resultset2Index the index of the second resultset
* @param comparisonColumn the column containing values to compare
* @return the results of the paired comparison
* @exception Exception if an error occurs
*/
public PairedStats calculateStatistics(Instance datasetSpecifier,
int resultset1Index,
int resultset2Index,
int comparisonColumn) throws Exception;
/**
* Creates a key that maps resultset numbers to their descriptions.
*
* @return a value of type 'String'
*/
public String resultsetKey();
/**
* Creates a "header" string describing the current resultsets.
*
* @param comparisonColumn a value of type 'int'
* @return a value of type 'String'
*/
public String header(int comparisonColumn);
/**
* Carries out a comparison between all resultsets, counting the number
* of datsets where one resultset outperforms the other.
*
* @param comparisonColumn the index of the comparison column
* @return a 2d array where element [i][j] is the number of times resultset
* j performed significantly better than resultset i.
* @exception Exception if an error occurs
*/
public int [][] multiResultsetWins(int comparisonColumn, int [][] nonSigWin)
throws Exception;
/**
* Carries out a comparison between all resultsets, counting the number
* of datsets where one resultset outperforms the other. The results
* are summarized in a table.
*
* @param comparisonColumn the index of the comparison column
* @return the results in a string
* @exception Exception if an error occurs
*/
public String multiResultsetSummary(int comparisonColumn)
throws Exception;
public String multiResultsetRanking(int comparisonColumn)
throws Exception;
/**
* Creates a comparison table where a base resultset is compared to the
* other resultsets. Results are presented for every dataset.
*
* @param baseResultset the index of the base resultset
* @param comparisonColumn the index of the column to compare over
* @return the comparison table string
* @exception Exception if an error occurs
*/
public String multiResultsetFull(int baseResultset,
int comparisonColumn) throws Exception;
/**
* Get the value of ResultsetKeyColumns.
*
* @return Value of ResultsetKeyColumns.
*/
public Range getResultsetKeyColumns();
/**
* Set the value of ResultsetKeyColumns.
*
* @param newResultsetKeyColumns Value to assign to ResultsetKeyColumns.
*/
public void setResultsetKeyColumns(Range newResultsetKeyColumns);
/**
* Gets the indices of the the datasets that are displayed (if null
* then all are displayed). The base is always displayed.
*
* @return the indices of the datasets to display
*/
public int[] getDisplayedResultsets();
/**
* Sets the indicies of the datasets to display (null
means all).
* The base is always displayed.
*
* @param cols the indices of the datasets to display
*/
public void setDisplayedResultsets(int[] cols);
/**
* Get the value of SignificanceLevel.
*
* @return Value of SignificanceLevel.
*/
public double getSignificanceLevel();
/**
* Set the value of SignificanceLevel.
*
* @param newSignificanceLevel Value to assign to SignificanceLevel.
*/
public void setSignificanceLevel(double newSignificanceLevel);
/**
* Get the value of DatasetKeyColumns.
*
* @return Value of DatasetKeyColumns.
*/
public Range getDatasetKeyColumns();
/**
* Set the value of DatasetKeyColumns.
*
* @param newDatasetKeyColumns Value to assign to DatasetKeyColumns.
*/
public void setDatasetKeyColumns(Range newDatasetKeyColumns);
/**
* Get the value of RunColumn.
*
* @return Value of RunColumn.
*/
public int getRunColumn();
/**
* Set the value of RunColumn.
*
* @param newRunColumn Value to assign to RunColumn.
*/
public void setRunColumn(int newRunColumn);
/**
* Get the value of FoldColumn.
*
* @return Value of FoldColumn.
*/
public int getFoldColumn();
/**
* Set the value of FoldColumn.
*
* @param newFoldColumn Value to assign to FoldColumn.
*/
public void setFoldColumn(int newFoldColumn);
/**
* Returns the name of the column to sort on.
*
* @return the name of the column to sort on.
*/
public String getSortColumnName();
/**
* Returns the column to sort on, -1 means the default sorting.
*
* @return the column to sort on.
*/
public int getSortColumn();
/**
* Set the column to sort on, -1 means the default sorting.
*
* @param newSortColumn the new sort column.
*/
public void setSortColumn(int newSortColumn);
/**
* Get the value of Instances.
*
* @return Value of Instances.
*/
public Instances getInstances();
/**
* Set the value of Instances.
*
* @param newInstances Value to assign to Instances.
*/
public void setInstances(Instances newInstances);
}