現放程式碼，後加註釋

package com.gk.dmMethod;

import java.io.BufferedReader;
import java.io.FileNotFoundException;
import java.io.FileReader;
import java.io.IOException;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.HashMap;
import java.util.Iterator;
import java.util.List;
import java.util.Map;

import
 
 com.sun.corba.se.impl.encoding.OSFCodeSetRegistry.Entry;

/**
*樸素貝葉斯：要預測的必須是分類屬性
*
*
*1.設定訓練集檔案，指定要預測屬性[預設最後一個為預測屬性]
*2.生成模型
*3.設定測試集檔案，[判斷檔案是否符合要求，有無缺失]
*4.預測，指定輸出[預設Console，輸出]
*
*
*/
public  class NaiveBayesian{

    private boolean isSetTrainSet;
    private boolean isModelGenerted;
    private boolean
 
 isSetTestSet;

    private String trainSet;
    private String testSet;

    private int num = -1;
    private int total_trainNum = 0; 
    Map<String, Double> mapProba = new HashMap<String,Double>();
    public NaiveBayesian(){
        isSetTestSet = false;
        isModelGenerted = false
 
;
        isSetTestSet = false;
    }

    public void setTrainSetFile(String trainSetFile) throws Exception{
        setTrainSet(trainSetFile);
        isSetTrainSet = true;
        isModelGenerted = false;
    }

    /**
     * 只是賦值
     * @param trainSet
     * @throws Exception
     */
    private void setTrainSet(String trainSet)throws Exception{
        this.trainSet = trainSet;
    }

    public void setTestSetFile(String testSetFile){
        setTestSet(testSetFile);
        isSetTestSet = true;
    }

    private void setTestSet(String testSet){
        this.testSet = testSet;
    }

    public void generatePredictedModel() throws IOException, Exception{
        //TODO generate the model
        BufferedReader reader;

            System.out.println(trainSet);
            reader = new BufferedReader(new FileReader(trainSet));
            String line ="";
            while((line= reader.readLine()) != null){
                addToMap(line);
            }
            reader.close();
            isModelGenerted = true;
        }






    private Map<String, ArrayList<AttributeS>> map = new HashMap<String,ArrayList<AttributeS>>();

    public void getModel(){
        String model ="";
        for(Map.Entry<String,ArrayList<AttributeS>> entry : map.entrySet()){
            System.out.println(entry.getKey());
            for(AttributeS attr:entry.getValue()){
                System.out.println(attr);
            }
            System.out.println();
        }
    }

    public void precdite()throws Exception{
        if(!isModelGenerted) throw new Exception("Haven't Generaten The PredicatedModel");
        if(!isSetTestSet) throw new Exception("Haven't set the Test File");

        //TODO precdite;
        double max =0;
        BufferedReader reader = new BufferedReader(new FileReader(testSet));;

        String line  = "";
        while((line = reader.readLine()) != null){
            String[] tokens = line.split(" ");
            //Map<String, ArrayList<AttributeS>> map = new HashMap<String,ArrayList<AttributeS>>();
//          System.out.println(Arrays.toString(tokens));
//          System.out.println();

            int sum =0;
            for(Map.Entry<String,ArrayList<AttributeS>> entry:map.entrySet()){
                sum +=entry.getValue().size(); 
                double temp = 1;
                double temp_1;
                for(int i =0;i<tokens.length;i++){
                    temp_1 = entry.getValue().get(i).getP(tokens[i]);
                    System.out.print(temp_1 + " * ");
                    temp *= entry.getValue().get(i).getP(tokens[i]);
                }
                System.out.println();
                System.out.println(mapProba.get(entry.getKey()));
                mapProba.put(entry.getKey(),temp * mapProba.get(entry.getKey()) / total_trainNum);
            }
//          System.out.println("sum:" + sum);
//          for(Map.Entry<String,ArrayList<AttributeS>> entry:map.entrySet()){
////                mapProba.put(entry.getKey(),);
//              double temp = entry.getValue().size() * 1.0 / sum;
//              System.out.println("============" + temp);
//              mapProba.put(entry.getKey(),mapProba.get(entry.getKey()) *temp );
//          }
//          System.out.println(line);
//          System.out.println("===================");
            for(Map.Entry<String,Double> entry:mapProba.entrySet()){
                System.out.println(entry.getKey() + " :\t"+entry.getValue());
            }
            System.out.println("===================");
            System.out.println();
        }
    }



    private void addToMap(String line) throws Exception{
//      System.err.println("add to map : " + line);
        String[] temp = line.split(" ");
        if(num == -1) num = temp.length;
        if(num != temp.length) throw new Exception("the file has some error  :" + line);
        int tempNum = num-1;
        int i =0;
        ArrayList<AttributeS> list =null;
        total_trainNum++;
        if(!mapProba.containsKey(temp[tempNum])) mapProba.put(temp[tempNum],(double) 1);
        else mapProba.put(temp[tempNum],mapProba.get(temp[tempNum]) + 1);
        if(!map.containsKey(temp[tempNum])) {
            list = new ArrayList<AttributeS>();
            for(i = 0;i < tempNum;i++){
                try{

                    Integer.parseInt(temp[i]);
                    list.add(new NumericalAttr());
                }catch(Exception e){
                    list.add(new CategoricalAttr());
                }
            }
            map.put(temp[tempNum], list);
        }// end if
        list = map.get(temp[tempNum]);
        for(i =0;i<tempNum;i++){
            list.get(i).add(temp[i]);
            map.put(temp[tempNum],list);
        }

        }
    }


    /*採用懶人設計模式，第一次呼叫的時候再例項化*/
    abstract class AttributeS{

        abstract void add(String attr) throws Exception;

        abstract double getP(String attribute) throws Exception;
    }

    class CategoricalAttr extends AttributeS{

        int sum =0;

        Map<String,Integer> map = new HashMap<String,Integer>();



        void add(String attr){
            sum++;
            if(!map.containsKey(attr)) map.put(attr,1);
            else map.put(attr,map.get(attr)+1);

        }

        double getP(String attribute) throws Exception{
            double result = 0;
            try{
                result = map.get(attribute) * 1.0 / sum;
            }catch(Exception e){
                throw new Exception("Can't find the attribute : " + attribute);
            }
            return result;
        }

        @Override
        public String toString() {

            for(Map.Entry<String,Integer> entry:map.entrySet()){
                System.out.print("<" + entry.getKey() + "," + entry.getValue()+">,");
            }
            return "";
        }
    }

    class NumericalAttr extends AttributeS{
        int sum;
        int n;
        double average;
        double vaiance;//方差
        double vaiance_standard;//標準差
        double temp_xi =0;
        List<Integer> list = new ArrayList<Integer>();
        boolean isComputed = false;



        void add(String attr) throws Exception{
            if(isComputed) throw new Exception("the model has been Computed");
            try{
                Integer temp = Integer.parseInt(attr);
                list.add(temp);
                temp_xi += temp * temp;
                sum+=temp;
            }catch(Exception e){
                throw new Exception("Some error in attribute");
            }
        }


        double getP(String attribute){
            //TODO
            if(isComputed){
                compute();
                isComputed = true;
            }
            int temp = Integer.parseInt(attribute);
            return Math.log(-(Math.pow((temp - average),2)) / (2 * vaiance)) / (vaiance_standard * Math.sqrt(2 * Math.PI));

        }

        private void compute(){
            average = sum * 1.0/ list.size();
            vaiance = average * average * list.size() + temp_xi - 2 * sum * average;
            vaiance_standard = Math.sqrt(vaiance);
        }

        @Override
        public String toString() {
            return list.toString();
        }
    }