id3决策树程序

Posted 2023-03-07

【中文标题】id3决策树程序

【英文标题】：id3 decision tree program

【发布时间】：2013-08-23 12:21:58

【问题描述】：

你能检查一下这个程序将在netbeans中运行没有任何错误。这个程序的输出将是什么。我试图运行这个程序但我得到的输出只读取我给输入文件的数据.arff file.im 得到如下输出：Read 0 data 最后一行阅读：@attribute handicapped-infants String,n,y 期望 2 个属性

import java.io.*;

import java.util.*;

public class ID3



int numAttributes;

String []attributeNames;

Vector []domains;

/* The class to represent a data point consisting of numAttributes values

of attributes */

class DataPoint 

public int []attributes;

public DataPoint(int numattributes) 

attributes = new int[numattributes];



;

/* The class to represent a node in the decomposition tree.

*/

class TreeNode 

public double entropy;

public Vector data;

public int decompositionAttribute;

public int decompositionValue;

public TreeNode []children;

public TreeNode parent;

public TreeNode() 

data = new Vector();



;

TreeNode root = new TreeNode();

public int getSymbolValue(int attribute, String symbol) 

int index = domains[attribute].indexOf(symbol);

if (index < 0) 

domains[attribute].addElement(symbol);

return domains[attribute].size() -1;



return index;



public int []getAllValues(Vector data, int attribute) 

Vector values = new Vector();

int num = data.size();

for (int i=0; i< num; i++) 

DataPoint point = (DataPoint)data.elementAt(i);

String symbol =

(String)domains[attribute].elementAt(point.attributes[attribute] );

int index = values.indexOf(symbol);

if (index < 0) 

values.addElement(symbol);





int []array = new int[values.size()];

for (int i=0; i< array.length; i++) 

String symbol = (String)values.elementAt(i);

array[i] = domains[attribute].indexOf(symbol);



values = null;

return array;



public Vector getSubset(Vector data, int attribute, int value) 

Vector subset = new Vector();

int num = data.size();

for (int i=0; i< num; i++) 

DataPoint point = (DataPoint)data.elementAt(i);

if (point.attributes[attribute] == value) subset.addElement(point);



return subset;



public double calculateEntropy(Vector data) 

int numdata = data.size();

if (numdata == 0) return 0;

int attribute = numAttributes-1;

int numvalues = domains[attribute].size();

double sum = 0;

for (int i=0; i< numvalues; i++) 

int count=0;

for (int j=0; j< numdata; j++) 

DataPoint point = (DataPoint)data.elementAt(j);

if (point.attributes[attribute] == i) count++;



double probability = 1.*count/numdata;

if (count > 0) sum += -probability*Math.log(probability);



return sum;



public boolean alreadyUsedToDecompose(TreeNode node, int attribute) 

if (node.children != null) 

if (node.decompositionAttribute == attribute )

return true;



if (node.parent == null) return false;

return alreadyUsedToDecompose(node.parent, attribute);



public void decomposeNode(TreeNode node) 

double bestEntropy=0;

boolean selected=false;

int selectedAttribute=0;

int numdata = node.data.size();

int numinputattributes = numAttributes-1;

node.entropy = calculateEntropy(node.data);

if (node.entropy == 0) return;

for (int i=0; i< numinputattributes; i++) 

int numvalues = domains[i].size();

if ( alreadyUsedToDecompose(node, i) ) continue;

double averageentropy = 0;

for (int j=0; j< numvalues; j++) 

Vector subset = getSubset(node.data, i, j);

if (subset.size() == 0) continue;

double subentropy = calculateEntropy(subset);

averageentropy += subentropy *

subset.size();



averageentropy = averageentropy / numdata; //

Taking the weighted average

if (selected == false) 

selected = true;

bestEntropy = averageentropy;

selectedAttribute = i;

 else 

if (averageentropy < bestEntropy) 

selected = true;

bestEntropy = averageentropy;

selectedAttribute = i;







if (selected == false) return;

int numvalues = domains[selectedAttribute].size();

node.decompositionAttribute = selectedAttribute;

node.children = new TreeNode [numvalues];

for (int j=0; j< numvalues; j++) 

node.children[j] = new TreeNode();

node.children[j].parent = node;

node.children[j].data = getSubset(node.data,

selectedAttribute, j);

node.children[j].decompositionValue = j;



for (int j=0; j< numvalues; j++) 

decomposeNode(node.children[j]);



node.data = null;



public int readData(String filename) throws Exception 

FileInputStream in = null;

try 

File inputFile = new File(filename);

in = new FileInputStream(inputFile);

 catch ( Exception e) 

System.err.println( "Unable to open data file: " + filename + "n" + e);

return 0;



BufferedReader bin = new BufferedReader(new InputStreamReader(in) );

String input;

while(true) 

input = bin.readLine();

if (input == null) 

System.err.println( "No data found in the data file: " + filename +

"n");

return 0;



if (input.startsWith("//")) continue;

if (input.equals("")) continue;

break;



StringTokenizer tokenizer = new StringTokenizer(input);

numAttributes = tokenizer.countTokens();

if (numAttributes <= 1) 

System.err.println( "Read line: " + input);

System.err.println( "Could not obtain the names of attributes in the

line");

System.err.println( "Expecting at least one input attribute and one

output attribute");

return 0;



domains = new Vector[numAttributes];

for (int i=0; i < numAttributes; i++) domains[i] = new Vector();

attributeNames = new String[numAttributes];

for (int i=0; i < numAttributes; i++) 

attributeNames[i] = tokenizer.nextToken();



while(true) 

input = bin.readLine();

if (input == null) break;

if (input.startsWith("//")) continue;

if (input.equals("")) continue;

tokenizer = new StringTokenizer(input);

int numtokens = tokenizer.countTokens();

if (numtokens != numAttributes) 

System.err.println( "Read " + root.data.size() + " data");

System.err.println( "Last line read: " + input);

System.err.println( "Expecting " + numAttributes + " attributes");

return 0;



DataPoint point = new DataPoint(numAttributes);

for (int i=0; i < numAttributes; i++) 

point.attributes[i] = getSymbolValue(i, tokenizer.nextToken()

);



root.data.addElement(point);



bin.close();

return 1;



public void printTree(TreeNode node, String tab) 

int outputattr = numAttributes-1;

if (node.children == null) 

int []values = getAllValues(node.data, outputattr );

if (values.length == 1) 

System.out.println(tab + "t" + attributeNames[outputattr] + " = "" +

domains[outputattr].elementAt(values[0]) + "";");

return;



System.out.print(tab + "t" + attributeNames[outputattr] + " = ");

for (int i=0; i < values.length; i++) 

System.out.print(""" + domains[outputattr].elementAt(values[i]) + ""

");

if ( i != values.length-1 ) System.out.print( " , " );



System.out.println( " ;");

return;



int numvalues = node.children.length;

for (int i=0; i < numvalues; i++) 

System.out.println(tab + "if( " +

attributeNames[node.decompositionAttribute] + " == "" +

domains[node.decompositionAttribute].elementAt(i)

+ "") " );

printTree(node.children[i], tab + "t");

if (i != numvalues-1) System.out.print(tab + " else ");

else System.out.println(tab + "");





public void createDecisionTree() 

decomposeNode(root);

printTree(root, "");



/* main function */

public static void main(String[] args) throws Exception 

ID3 me = new ID3();

int status = me.readData("c:\\in.txt");

if (status <= 0) return;

me.createDecisionTree();

【参考方案1】：

输出将是一棵树。但是，您需要向其传递至少具有 2 个属性的文件。