Java實現(xiàn)的樸素貝葉斯算法示例
本文實例講述了Java實現(xiàn)的樸素貝葉斯算法。分享給大家供大家參考,具體如下:
對于樸素貝葉斯算法相信做數(shù)據(jù)挖掘和推薦系統(tǒng)的小伙們都耳熟能詳了,算法原理我就不啰嗦了。我主要想通過java代碼實現(xiàn)樸素貝葉斯算法,思想:
1. 用javabean +Arraylist 對于訓(xùn)練數(shù)據(jù)存儲
2. 對于樣本數(shù)據(jù)訓(xùn)練
具體的代碼如下:
package NB; /** * 訓(xùn)練樣本的屬性 javaBean * */ public class JavaBean { int age; String income; String student; String credit_rating; String buys_computer; public JavaBean(){ } public JavaBean(int age,String income,String student,String credit_rating,String buys_computer){ this.age=age; this.income=income; this.student=student; this.credit_rating=credit_rating; this.buys_computer=buys_computer; } public int getAge() { return age; } public void setAge(int age) { this.age = age; } public String getIncome() { return income; } public void setIncome(String income) { this.income = income; } public String getStudent() { return student; } public void setStudent(String student) { this.student = student; } public String getCredit_rating() { return credit_rating; } public void setCredit_rating(String credit_rating) { this.credit_rating = credit_rating; } public String getBuys_computer() { return buys_computer; } public void setBuys_computer(String buys_computer) { this.buys_computer = buys_computer; } @Override public String toString() { return "JavaBean [age=" + age + ", income=" + income + ", student=" + student + ", credit_rating=" + credit_rating + ", buys_computer=" + buys_computer + "]"; } }
算法實現(xiàn)的部分:
package NB; import java.io.BufferedReader; import java.io.File; import java.io.FileReader; import java.util.ArrayList; public class TestNB { /**data_length * 算法的思想 */ public static ArrayList<JavaBean> list = new ArrayList<JavaBean>();; static int data_length=0; public static void main(String[] args) { // 1.讀取數(shù)據(jù),放入list容器中 File file = new File("E://test.txt"); txt2String(file); //數(shù)據(jù)測試樣本 testData(25,"Medium","Yes","Fair"); } // 讀取樣本數(shù)據(jù) public static void txt2String(File file) { try { BufferedReader br = new BufferedReader(new FileReader(file));// 構(gòu)造一個BufferedReader類來讀取文件 String s = null; while ((s = br.readLine()) != null) {// 使用readLine方法,一次讀一行 data_length++; splitt(s); } br.close(); } catch (Exception e) { e.printStackTrace(); } } // 存入ArrayList中 public static void splitt(String str){ String strr = str.trim(); String[] abc = strr.split("[\\p{Space}]+"); int age=Integer.parseInt(abc[0]); JavaBean bean=new JavaBean(age, abc[1], abc[2], abc[3], abc[4]); list.add(bean); } // 訓(xùn)練樣本,測試 public static void testData(int age,String a,String b,String c){ //訓(xùn)練樣本 int number_yes=0; int bumber_no=0; // age情況 個數(shù) int num_age_yes=0; int num_age_no=0; // income int num_income_yes=0; int num_income_no=0; // student int num_student_yes=0; int num_stdent_no=0; //credit int num_credit_yes=0; int num_credit_no=0; //遍歷List 獲得數(shù)據(jù) for(int i=0;i<list.size();i++){ JavaBean bb=list.get(i); if(bb.getBuys_computer().equals("Yes")){ //Yes number_yes++; if(bb.getIncome().equals(a)){//income num_income_yes++; } if(bb.getStudent().equals(b)){//student num_student_yes++; } if(bb.getCredit_rating().equals(c)){//credit num_credit_yes++; } if(bb.getAge()==age){//age num_age_yes++; } }else {//No bumber_no++; if(bb.getIncome().equals(a)){//income num_income_no++; } if(bb.getStudent().equals(b)){//student num_stdent_no++; } if(bb.getCredit_rating().equals(c)){//credit num_credit_no++; } if(bb.getAge()==age){//age num_age_no++; } } } System.out.println("購買的歷史個數(shù):"+number_yes); System.out.println("不買的歷史個數(shù):"+bumber_no); System.out.println("購買+age:"+num_age_yes); System.out.println("不買+age:"+num_age_no); System.out.println("購買+income:"+num_income_yes); System.out.println("不買+income:"+num_income_no); System.out.println("購買+stundent:"+num_student_yes); System.out.println("不買+student:"+num_stdent_no); System.out.println("購買+credit:"+num_credit_yes); System.out.println("不買+credit:"+num_credit_no); //// 概率判斷 double buy_yes=number_yes*1.0/data_length; // 買的概率 double buy_no=bumber_no*1.0/data_length; // 不買的概率 System.out.println("訓(xùn)練數(shù)據(jù)中買的概率:"+buy_yes); System.out.println("訓(xùn)練數(shù)據(jù)中不買的概率:"+buy_no); /// 未知用戶的判斷 double nb_buy_yes=(1.0*num_age_yes/number_yes)*(1.0*num_income_yes/number_yes)*(1.0*num_student_yes/number_yes)*(1.0*num_credit_yes/number_yes)*buy_yes; double nb_buy_no=(1.0*num_age_no/bumber_no)*(1.0*num_income_no/bumber_no)*(1.0*num_stdent_no/bumber_no)*(1.0*num_credit_no/bumber_no)*buy_no; System.out.println("新用戶買的概率:"+nb_buy_yes); System.out.println("新用戶不買的概率:"+nb_buy_no); if(nb_buy_yes>nb_buy_no){ System.out.println("新用戶買的概率大"); }else { System.out.println("新用戶不買的概率大"); } } }
對于樣本數(shù)據(jù):
25 High No Fair No
25 High No Excellent No
33 High No Fair Yes
41 Medium No Fair Yes
41 Low Yes Fair Yes
41 Low Yes Excellent No
33 Low Yes Excellent Yes
25 Medium No Fair No
25 Low Yes Fair Yes
41 Medium Yes Fair Yes
25 Medium Yes Excellent Yes
33 Medium No Excellent Yes
33 High Yes Fair Yes
41 Medium No Excellent No
對于未知用戶的數(shù)據(jù)得出的結(jié)果:
購買的歷史個數(shù):9
不買的歷史個數(shù):5
購買+age:2
不買+age:3
購買+income:4
不買+income:2
購買+stundent:6
不買+student:1
購買+credit:6
不買+credit:2
訓(xùn)練數(shù)據(jù)中買的概率:0.6428571428571429
訓(xùn)練數(shù)據(jù)中不買的概率:0.35714285714285715
新用戶買的概率:0.028218694885361547
新用戶不買的概率:0.006857142857142858
新用戶買的概率大
更多關(guān)于java算法相關(guān)內(nèi)容感興趣的讀者可查看本站專題:《Java數(shù)據(jù)結(jié)構(gòu)與算法教程》、《Java操作DOM節(jié)點技巧總結(jié)》、《Java文件與目錄操作技巧匯總》和《Java緩存操作技巧匯總》
希望本文所述對大家java程序設(shè)計有所幫助。
相關(guān)文章
Spring使用注解進(jìn)行引用類型的自動裝配逐步分析
自動裝配是springboot的核心,一般提到自動裝配就會和springboot聯(lián)系在一起。實際上Spring Framework早就實現(xiàn)了這個功能。Spring Boot只是在其基礎(chǔ)上,通過SPI的方式,做了進(jìn)一步優(yōu)化2023-03-03Java中的synchronized有幾種加鎖方式(實例詳解)
在Java中,synchronized關(guān)鍵字提供了內(nèi)置的支持來實現(xiàn)同步訪問共享資源,以避免并發(fā)問題,這篇文章主要介紹了java的synchronized有幾種加鎖方式,需要的朋友可以參考下2024-05-05