Apiori_Java.rar_关联规则

/** * Copyright (c) 2003 HCYCOM, Inc. All Rights Reserved. * * A Java application of Apriori algorithm. * * Make sure that your DBMS Service is running before the OS loads the program. * Either SQLServer2000 or MySQL4.0 is your good start. * * @author Zengli, China Agricultural University. * @version 0.01 03/07/09 * * mailto:zengli@hcycom.com */ import java.sql.*; import java.util.*; import java.math.*; public class Apriori { Connection conn; int rowCount; private String url,user,passwd; String[] itemList = null; int[] itemCount = null; final double MIN_SUP = 0.4;//最小支持度s final double MIN_CONF = 0.5;//最小置信度c PreparedStatement pstmt = null; ResultSet rs = null; //定义结果集 PreparedStatement ckPstmt = null; ResultSet ckRs = null; PreparedStatement lkPstmt = null; //构造函数 Apriori() { url = "jdbc:odbc:AprioriMySQL";//定义JDBC-ODBC桥的URL user = "root"; passwd = ""; conn = null; rowCount = 0; //预设项列表(商品集)={啤酒,尿布,擦身粉,面包,雨伞,牛奶,洗衣粉,可乐} itemList = new String[]{"beer","diaper","toiletpowder","bread","umbrella","milk","washingpowder","coke"}; itemCount = new int[itemList.length]; } public static void main(String[] args) { Apriori a = new Apriori(); a.execute(); } //加载指定的数据库驱动程序 void loadJdbcOdbcDriver(String driverName) { try{ System.out.println("加载数据库驱动程序 ...OK!"); Class.forName(driverName); } catch(java.lang.ClassNotFoundException e){ System.err.print("ClassNotFoundException:"); System.err.println(e.getMessage()); } } //Apriori算法实现 void execute() { //加载数据库驱动程序 loadJdbcOdbcDriver("sun.jdbc.odbc.JdbcOdbcDriver"); System.out.println("初次扫描数据库commodity ...OK!\n"); try{ //建立连接ODBC数据源 conn = DriverManager.getConnection(url,user,passwd); //提交连接请求 conn.setAutoCommit(false); //------- 初次扫描数据库commodity的transaction表,对每个候选(即商品项)以及事务(即交易)计数 ------ pstmt = conn.prepareStatement("SELECT * FROM transaction",ResultSet.TYPE_SCROLL_SENSITIVE,ResultSet.CONCUR_UPDATABLE); rs = pstmt.executeQuery(); int id; String commodity_list; Statement stmt5 = null; Statement stmt8 = null; Statement stmt9 = null; stmt5 = conn.createStatement(); stmt5.execute("DELETE FROM lk"); for (int i = 0; i < itemList.length; i++){ rowCount = 0; while (rs.next()){ id = rs.getInt(1); commodity_list = rs.getString("commodity_list"); if (commodity_list.indexOf(itemList[i]) != -1) itemCount[i]++;//对每个候选计数 rowCount++; } System.out.println(itemList[i] + "\t\t\t(" + itemCount[i] + ")"); //比较候选支持度计数与最小支持度计数,得出L1表 if (itemCount[i] >= (int)(MIN_SUP * rowCount)){ pstmt = conn.prepareStatement("INSERT INTO Lk(itemsets,sup_count) VALUES(?,?)",ResultSet.TYPE_SCROLL_SENSITIVE,ResultSet.CONCUR_UPDATABLE); pstmt.setString(1,itemList[i]); pstmt.setInt(2,itemCount[i]); pstmt.executeUpdate(); } rs.beforeFirst(); } //------- 算法核心 : 使用候选项集Ck找频繁项集Lk ------- for (int k = 2; ; k++){ if (!aproiri_gen(k - 1, MIN_SUP)) break;//连接-剪枝生成候选集Ck(即Ck表) //读取Ck表的每一个候选项集 pstmt = conn.prepareStatement("SELECT * FROM ck",ResultSet.TYPE_SCROLL_SENSITIVE,ResultSet.CONCUR_UPDATABLE); rs = pstmt.executeQuery(); stmt8 = conn.createStatement(); stmt8.execute("DELETE FROM lk");//清空旧的Lk表(即Lk-1表) while (rs.next()){ String ck = rs.getString("itemsets");//读出Ck中每个候选项集(即Ck表的第一个字段) //将Ck当前候选项集中各元素分离并复制到Vector向量的各分量中 Vector ckItemList = new Vector(k); ckItemList = splitItemList(k, ck); int ckSupCnt = 0;//Ck项集支持度 //扫描数据库commodity的transaction表,为Ck中的每个候选项集计数 ckPstmt = conn.prepareStatement("SELECT * FROM transaction",ResultSet.TYPE_SCROLL_SENSITIVE,ResultSet.CONCUR_UPDATABLE); ckRs = ckPstmt.executeQuery(); while (ckRs.next()){//循环读入transaction表的记录 String s = ckRs.getString("commodity_list");//得到commodity_list字段内容 System.out.println("commodity_field = "+s); int j = 0; for (; j < k; j++){ if (s.indexOf(ckItemList.elementAt(j).toString()) == -1) break;//扫描当前记录,判断是否同时存在Ck当前候选项集中的所有元素 } if (j >= k) ckSupCnt++;//Ck候选项集支持度计数 } //比较候选支持度计数与最小支持度计数,生成新的Lk表 System.out.println("ckSupCnt = " + ckSupCnt +" (int)(MIN_SUP * rowCount)=" +(int)(MIN_SUP * rowCount)); if (ckSupCnt >= (int)(MIN_SUP * rowCount)){ stmt9 = conn.createStatement(); stmt9.execute("INSERT INTO lk(itemsets,sup_count) VALUES('" + ck + "'," + ckSupCnt + ")"); } } } //操作语句提交 conn.commit(); conn.setAutoCommit(true); if (ckPstmt != null) ckPstmt.close(); if (lkPstmt != null) lkPstmt.close(); if (pstmt != null) pstmt.close(); if (conn != null) conn.close(); System.out.println("-- END --"); } catch(BatchUpdateException b){ System.err.println("--BatchUpdateException--"); System.err.println("SQLState: " + b.getSQLState()); System.err.println("Message: " + b.getMessage()); System.err.println("Vendor: " + b.getErrorCode()); System.err.print("Update counts: "); int [] updateCounts = b.getUpdateCounts(); for(int i = 0; i<updateCounts.length;i++){ System.err.print(updateCounts[i] + " "); } System.err.println(""); } catch(SQLException ex){ System.err.println("--SQLException--"); System.err.println("SQLState: " + ex.getSQLState()); System.err.println("Message: " + ex.getMessage()); System.err.println("Vendor: " + ex.getErrorCode()); } } //连接-剪枝动作,产生候选k-项集(即得到Ck表) boolean aproiri_gen(int k, double min_sup) { ResultSet lkRs1 = null; ResultSet lkRs2 = null; int ckCnt = 0; Statement stmt = null; Statement stmt2 = null; Statement stmt7 = null; try{ //读取旧Lk表(即Lk-1表)中的所有项集 stmt = conn.createStatement(); lkRs1 = stmt.executeQuery("SELECT * FROM lk"); stmt7 = conn.createStatement(); stmt7.execute("DELETE FROM ck"); ResultSet tRs1 = lkRs1; while (lkRs1.next()){ String lkItemsets1 = lkRs1.getString("itemsets");//读取当前lkRs1结果集记录的第一个字段 stmt2 = conn.createStatement(); lkRs2 = stmt2.executeQuery("SELECT * FROM lk"); while (lkRs2.next()){ String lkItemsets2 = lkRs2.getString("itemsets");//读取当前lkRs2结果集记录的第一个字段 if (isLinkable(k, lkItemsets1, lkItemsets2)){//判断当前lkRs1项集与当前lkRs2项集是否存在可连接性 System.out.println("k="+ k +" lkItemsets1 = "+ lkItemsets1 + " lkItemsets2= "+ lkItemsets2); if (!pruneAction(joinAction(k, lkItemsets1, lkItemsets2), tRs1)) ckCnt++;//连接-剪枝;统计剪枝后剩余的Ck项集数 } else break;//不存在可连接性则中断本次lkRs2结果集循环 } } } catch(Exception e){ e.printStackTrace(); } System.out.println("ckCnt=" + ckCnt); if (ckCnt == 0) return false;//如剪枝后Ck项集的计数值为0则算法终止 else return true; } //分离字符串并返回到向量中 Vector splitItemList(int k, String cl) { String[] strArray = cl.split(","); Vector v = new Vector(Arrays.asList(strArray));//将字符串数组转换为向量 System.out.println("splitItem = "+v); return v; } //判断是否具有可连接性 boolean isLinkable(int k, String s1,String s2) { Vector v1 = splitItemList(k, s1); Vector v2 = splitItemList(k,