package ca.pfv.spmf.algorithms.classifiers.decisiontree.id3;
/* This file is copyright (c) 2008-2012 Philippe Fournier-Viger
*
* This file is part of the SPMF DATA MINING SOFTWARE
* (http://www.philippe-fournier-viger.com/spmf).
*
* SPMF 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.
*
* SPMF 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
* SPMF. If not, see <http://www.gnu.org/licenses/>.
*/
/**
* This class represents a decision tree created by the ID3 algorithm.
*
* @see AlgoID3
* @see Node
* @see DecisionNode
* @see ClassNode
* @author Philippe Fournier-Viger
*/
public class DecisionTree {
// the list of attributes that was used to create the decision tree
String []allAttributes;
// a reference to the root node of the tree
Node root = null;
/**
* Print the tree to System.out.
*/
public void print() {
System.out.println("DECISION TREE");
String indent = " ";
print(root, indent, "");
}
/**
* Print a sub-tree to System.out
* @param nodeToPrint the root note
* @param indent the current indentation
* @param value a string that should be used to increase the indentation
*/
private void print(Node nodeToPrint, String indent, String value) {
if(value.isEmpty() == false)
System.out.println(indent + value);
String newIndent = indent + " ";
// if it is a class node
if(nodeToPrint instanceof ClassNode){
// cast to a class node and print it
ClassNode node = (ClassNode) nodeToPrint;
System.out.println(newIndent + " ="+ node.className);
}else{
// if it is a decision node, cast it to a decision node
// and print it.
DecisionNode node = (DecisionNode) nodeToPrint;
System.out.println(newIndent + allAttributes[node.attribute] + "->");
newIndent = newIndent + " ";
// then recursively call the method for subtrees
for(int i=0; i< node.nodes.length; i++){
print(node.nodes[i], newIndent, node.attributeValues[i]);
}
}
}
/**
* This method predict the class of an instance.
* @param newInstance an instance for which to perform the prediction.
* @return Return the class name or null if the tree cannot predict the class, for example because
* some value does not appear in the tree.
*/
public String predictTargetAttributeValue(String[] newInstance) {
return predict(root, newInstance);
}
/**
* Helper method to perform a prediction.
* @param currentNode the current node from the decision tree that is considered
* @param newInstance an instance for which to perform the prediction.
* @return Return the class name or null if the tree cannot predict the class, for example because
* some value does not appear in the tree.
*/
private String predict(Node currentNode, String[] newInstance) {
// If this node is a class node, then return the class name
if(currentNode instanceof ClassNode){
ClassNode node = (ClassNode) currentNode;
return node.className;
}else{
// otherwise, check which subtree we should follow
// by comparing the attribute of the instance
// with the one in the tree
DecisionNode node = (DecisionNode) currentNode;
String value = newInstance[node.attribute];
for(int i=0; i< node.attributeValues.length; i++){
if(node.attributeValues[i].equals(value)){
return predict(node.nodes[i], newInstance);
}
}
}
return null; // null if no subtree correspond to the attribute value for the instance
}
}