samoa-api/src/main/java/org/apache/samoa/learners/classifiers/trees/Node.java

/*
 * Licensed to the Apache Software Foundation (ASF) under one
 * or more contributor license agreements.  See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you 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.  See the License for the
 * specific language governing permissions and limitations
 * under the License.
 */

package org.apache.samoa.learners.classifiers.trees;

import org.apache.samoa.core.DoubleVector;
import org.apache.samoa.instances.Instance;

/**
 * Abstract class that represents a node in the tree model.
 * 
 * @author Arinto Murdopo
 * 
 */
public abstract class Node implements java.io.Serializable {

  private static final long serialVersionUID = 4008521239214180548L;

  protected final DoubleVector observedClassDistribution;

  /**
   * Method to route/filter an instance into its corresponding leaf. This method will be invoked recursively.
   * 
   * @param inst
   *          Instance to be routed
   * @param parent
   *          Parent of the current node
   * @param parentBranch
   *          The index of the current node in the parent
   * @return FoundNode which is the data structure to represent the resulting leaf.
   */
  public abstract FoundNode filterInstanceToLeaf(Instance inst, SplitNode parent, int parentBranch);

  /**
   * Method to return the predicted class of the instance based on the statistic inside the node.
   * 
   * @param inst
   *          To-be-predicted instance
   * @param map
   *          ModelAggregatorProcessor
   * @return The prediction result in the form of class distribution
   */
  abstract double[] getClassVotes(Instance inst, ModelAggregatorProcessor map);

  /**
   * Method to check whether the node is a leaf node or not.
   * 
   * @return Boolean flag to indicate whether the node is a leaf or not
   */
  abstract boolean isLeaf();

  /**
   * Constructor of the tree node
   * 
   * @param classObservation
   *          distribution of the observed classes.
   */
  protected Node(double[] classObservation) {
    this.observedClassDistribution = new DoubleVector(classObservation);
  }

  /**
   * Getter method for the class distribution
   * 
   * @return Observed class distribution
   */
  public double[] getObservedClassDistribution() {
    return this.observedClassDistribution.getArrayCopy();
  }

  /**
   * A method to check whether the class distribution only consists of one class or not.
   * 
   * @return Flag whether class distribution is pure or not.
   */
  public boolean observedClassDistributionIsPure() {
    return (observedClassDistribution.numNonZeroEntries() < 2);
  }

  protected void describeSubtree(ModelAggregatorProcessor modelAggrProc, StringBuilder out, int indent) {
    // TODO: implement method to gracefully define the tree
  }

  // TODO: calculate promise for limiting the model based on the memory size
  // double calculatePromise();
}