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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 .
*/
/*
* SplitEvaluator.java
* Copyright (C) 1999-2012 University of Waikato, Hamilton, New Zealand
*
*/
package weka.experiment;
import java.io.Serializable;
import weka.core.Instances;
/**
* Interface to objects able to generate a fixed set of results for
* a particular split of a dataset. The set of results should contain
* fields related to any settings of the SplitEvaluator (not including
* the dataset name. For example, one field for the classifier used to
* get the results, another for the classifier options, etc).
*
* Possible implementations of SplitEvaluator:
*
* - StdClassification results
*
- StdRegression results
*
*
* @author Len Trigg ([email protected])
* @version $Revision: 8034 $
*/
public interface SplitEvaluator extends Serializable {
/**
* Sets a list of method names for additional measures to look for
* in SplitEvaluators.
* @param additionalMeasures a list of method names
*/
void setAdditionalMeasures(String [] additionalMeasures);
/**
* Gets the names of each of the key columns produced for a single run.
* The names should not contain spaces (use '_' instead for easy
* translation.) The number of key fields must be constant for a given
* SplitEvaluator.
*
* @return an array containing the name of each key column
*/
String [] getKeyNames();
/**
* Gets the data types of each of the key columns produced for a single run.
* The number of key fields must be constant
* for a given SplitEvaluator.
*
* @return an array containing objects of the type of each key column. The
* objects should be Strings, or Doubles.
*/
Object [] getKeyTypes();
/**
* Gets the names of each of the result columns produced for a single run.
* The names should not contain spaces (use '_' instead for easy
* translation.) The number of result fields must be constant
* for a given SplitEvaluator.
*
* @return an array containing the name of each result column
*/
String [] getResultNames();
/**
* Gets the data types of each of the result columns produced for a
* single run. The number of result fields must be constant
* for a given SplitEvaluator.
*
* @return an array containing objects of the type of each result column.
* The objects should be Strings, or Doubles.
*/
Object [] getResultTypes();
/**
* Gets the key describing the current SplitEvaluator. For example
* This may contain the name of the classifier used for classifier
* predictive evaluation. The number of key fields must be constant
* for a given SplitEvaluator.
*
* @return a value of type 'Object'
*/
Object [] getKey();
/**
* Gets the results for the supplied train and test datasets.
*
* @param train the training Instances.
* @param test the testing Instances.
* @return the results stored in an array. The objects stored in
* the array may be Strings, Doubles, or null (for the missing value).
* @exception Exception if a problem occurs while getting the results
*/
Object [] getResult(Instances train, Instances test) throws Exception;
/**
* Returns the raw output for the most recent call to getResult. Useful
* for debugging splitEvaluators.
*
* @return the raw output corresponding to the most recent call
* to getResut
*/
String getRawResultOutput();
} // SplitEvaluator