数据挖掘—概念学习Candidate-Elimination算法的C++实现
Candidate-Elimination算法是数据挖掘中的一种概念学习算法，部分解决Find-S的不足，可以输出所有与训练样本一致的概念，同时利用概念间偏序关系来指导搜索，其伪代码描述如下
Initialize Gto the set of most-general hypotheses in H Initialize Sto the set of most-specific hypotheses in H For each training example, d, do: If dis a positive example then: Remove from Gany hypotheses that do not match d For each hypothesis sin Sthat does not match d Remove sfrom S Add to S all minimal generalizations, h, of ssuch that: 1) h matches d 2) some member of Gis more general than h Remove fromSany hthat is more general than another hypothesis in S If dis a negative example then: Remove from Sany hypotheses that match d For each hypothesis gin Gthat matches d Remove gfrom G Add to G all minimal specializations, h, of gsuch that: 1) hdoes not match d 2) some member of Sis more specific than h Remove fromG any hthat is more specific than another hypothesis in G
花了几个小时的时间总算把这个算法用C++实现测试通过了，采用了STL中的二维Vector容器保存字符串，在调试部分浪费不少时间。主要是用VC++ 6.0查看STL容器中的变量值不太方便，比如Vector，需要在调式窗口里输入s._first,10 才可以看到全部的数据；也可以加输出的测试代码，但是比较麻烦。好了，废话不多说了，贴上代码，希望各位批评指正。
【概念挖掘需求】
基本的算法思想是，泛化边界初始化为全？，特化边界特化为全空集(@),
1、若遇到正实例,首先从G中删除不包含该实例的概念，然后对S删除与实例不相符的概念，同时做最小泛化，使其包含该实例
2、若遇到负实例,首先从S中删除包含了该实例的概念，然后对G删除包含了该实例的概念，同时做最小特化，注意最小特化集是与当前S一一枚举出可能的特化概念，删除那些符合该实例的概念
C++源码
#include <iostream>
#include <string>
#include <vector>
using namespace std;
#define MAXLEN 7//输入每行的数据个数
//每行为标号 outlook Temperature Humidity Wind PlayTennis Swiming
//采用二维动态数组Vector保存处理
vector <vector <string> > state;//实例集
vector <vector <string> > S;//特化边界
vector <vector <string> > G;//泛化边界
vector <string> item(MAXLEN);//对应一行实例集
string yes("Yes");
string all("?");
string white("@");//@表示空集
string end("end");//输入结束
//判定概念h是否包含实例d
bool checkInclude(vector <string> h, vector <string> d){
bool res = true;
for(int i = 1; i < MAXLEN-1; i++){
if(!h[i].compare(all) || !h[i].compare(d[i])) continue;
else if(!h[i].compare(white) || h[i].compare(d[i])) res = false;
else {
cerr<<"error in checkInclude"<<endl;
res = false;
}
}
return res;
}
//对概念S[offset]做最小泛化，使得S[offset]包含d
void doMinGeneral(int offset, vector <string> d){
for(int i = 1; i < MAXLEN-1; i++){
if(!S[offset][i].compare(white)) {
S[offset][i] = d[i];
}
else if(S[offset][i].compare(d[i])) S[offset][i] = all;
else continue;//包括相等和h[i]为all的情况
}
}
//对概念G[offset]做最小特化，使得G[offset]包不含d，注意最小特化来自于和S的组合
void doMinSpecific(int offset, vector <string> d, vector <string> s){
for(int i = 1; i < MAXLEN-1; i++){
if(G[offset][i].compare(s[i]) && !G[offset][i].compare(all)){
if(s[i].compare(d[i])){
//产生新的泛化边界，注意不唯一
vector<string> temp (G[offset]);//先拷贝一份G[offset]
temp[i] = s[i];
G.push_back(temp);
}
}
if(G[offset][i].compare(s[i]) && G[offset][i].compare(all)){
cerr<<"doMinSpecific: error in data"<<endl;//G[offset][i]不为？且其与s[i]不同的情况
}
}
}
void input(){
int i, j;
string s;
while(cin>>s,s.compare(end) != 0){//-1为输入结束
item[0] = s;
for( i = 1;i < MAXLEN; i++){
cin>>item[i];
}
state.push_back(item);
}
//初始化
for( i = 0;i < MAXLEN; i++){
item[i] = white;
}
S.push_back(item);
for( i = 0;i < MAXLEN; i++){
item[i] = all;
}
G.push_back(item);
}
void output(){
int i,j;
cout<<"The specific boundary is:"<<endl;
for(i = 0; i < S.size(); i++){
for(j = 1;j < MAXLEN-1; j++){
cout<<S[i][j]<<" ";
}
cout<<endl;
}
cout<<endl;
cout<<"The general boundary is:"<<endl;
for(i = 0; i < G.size(); i++){
for(j = 1;j < MAXLEN-1; j++){
cout<<G[i][j]<<" ";
}
cout<<endl;
}
cout<<endl;
}
void solve(){
int i,j;
for( i = 0; i < state.size(); i++){
if(!state[i][MAXLEN-1].compare(yes)){
//正实例的情况,首先从G中删除不包含该实例的概念，
//然后对S删除与实例不相符的概念，同时做最小泛化，使其包含该实例
for(j = 0; j < G.size(); j++){
if(!checkInclude(G[j],state[i])) {
G.erase(G.begin() + j);
}
}
for(j = 0; j < S.size(); j++){
doMinGeneral(j,state[i]);
}
}
else {//负实例的情况,首先从S中删除包含了该实例的概念，
//然后对G做最小特化，与当前S一一枚举出可能的特化概念，删除那些符合该实例的概念
for(j = 0; j < S.size(); j++){
if(checkInclude(S[j],state[i])){
S.erase(S.begin() + j);
}
}
int orginGSize = G.size();//先记下G原始大小
for(j = 0; j < orginGSize; j++){
doMinSpecific(j,state[i],S[0]);
}
G.erase(G.begin(), G.begin() + (orginGSize));//删除G[0]到G[orginGSize-1],但是要注意括号内的参数不同
}
}
}
int main(){
input();
solve();
output();
return 0;
}
测试数据一
0 Sunny Warm High Strong Warm Yes 1 Sunny Warm Normal Strong Warm No 2 Rainy Cold High Strong Warm No 3 Sunny Warm High Strong Cool Yes end
测试结果一
The specific boundary is: Sunny Warm High Strong ? The general boundary is: Sunny ? High ? ? ? Warm High ? ?
测试数据二
0 Sunny Warm High Strong Warm Yes 1 Sunny Warm Normal Strong Warm No 2 Rainy Cold High Strong Warm No 3 Sunny Warm High Strong Cool Yes end测试结果二
The specific boundary is: Sunny Warm High Strong ? The general boundary is: Sunny ? High ? ? ? Warm High ? ?
具体预测的方法是
1、如果给定的实例符合概念集合S，则一定去游泳
2、如果给定的实例不符合概念集合G，则一定不去游泳
3、如果给定的实例不符合概念集合S，但是符合概念集合G，则可能去游泳