AttributeClassObserver.java

package org.apache.samoa.moa.classifiers.core.attributeclassobservers;

/*
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 * SAMOA
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 * Copyright (C) 2014 - 2015 Apache Software Foundation
 * %%
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 * 
 *      http://www.apache.org/licenses/LICENSE-2.0
 * 
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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import org.apache.samoa.moa.classifiers.core.AttributeSplitSuggestion;
import org.apache.samoa.moa.classifiers.core.splitcriteria.SplitCriterion;
import org.apache.samoa.moa.options.OptionHandler;

/**
 * Interface for observing the class data distribution for an attribute. This observer monitors the class distribution
 * of a given attribute. Used in naive Bayes and decision trees to monitor data statistics on leaves.
 * 
 * @author Richard Kirkby (rkirkby@cs.waikato.ac.nz)
 * @version $Revision: 7 $
 */
public interface AttributeClassObserver extends OptionHandler {

  /**
   * Updates statistics of this observer given an attribute value, a class and the weight of the instance observed
   * 
   * @param attVal
   *          the value of the attribute
   * @param classVal
   *          the class
   * @param weight
   *          the weight of the instance
   */
  public void observeAttributeClass(double attVal, int classVal, double weight);

  /**
   * Gets the probability for an attribute value given a class
   * 
   * @param attVal
   *          the attribute value
   * @param classVal
   *          the class
   * @return probability for an attribute value given a class
   */
  public double probabilityOfAttributeValueGivenClass(double attVal,
      int classVal);

  /**
   * Gets the best split suggestion given a criterion and a class distribution
   * 
   * @param criterion
   *          the split criterion to use
   * @param preSplitDist
   *          the class distribution before the split
   * @param attIndex
   *          the attribute index
   * @param binaryOnly
   *          true to use binary splits
   * @return suggestion of best attribute split
   */
  public AttributeSplitSuggestion getBestEvaluatedSplitSuggestion(
      SplitCriterion criterion, double[] preSplitDist, int attIndex,
      boolean binaryOnly);

  public void observeAttributeTarget(double attVal, double target);

}