/*试图用EM算法来根据输入的身高来区分性别*/#include<iostream>#include<fstream>#include<algorithm>#include<vector>using namespace std;#define PI 3.14159#define max(x,y) (x > y ? x : y)typedef struct FLOAT2{    float f1;    float f2;}FLOAT2;typedef struct Gaussian{    float mean;    float var;}Gaussian;typedef struct EMData{    char sex;    float fHeight;}EMData;//获取身高性别数据int getdata(vector<EMData> &Data){    ifstream fin;    fin.open("data.txt");    if(!fin)    {        cout<<"error: can‘t open the file."<<endl;        return -1;    }    while(!fin.eof())    {        char c[10];        float height;        fin >> c >> height;        EMData data;        data.sex = c[0];        data.fHeight = height;        Data.push_back(data);    }    return 0;}//根据身高数据区分性别, 返回正确率float predict(vector<EMData> Data){    //设符合正态分布    Gaussian sex[2];    float a[2]; //男女生所占百分比    float t = 1;    float tlimit = 0.000001; //收敛条件    //赋初值 下标0表示男生 1表示女生    sex[0].mean = 180.0;    sex[0].var = 10.0;    sex[1].mean = 150.0;    sex[1].var = 10.0;    a[0] = 0.5;    a[1] = 0.5;    while(t > tlimit)    {        Gaussian sex_old[2];        float a_old[2];        sex_old[0] = sex[0];        sex_old[1] = sex[1];        a_old[0] = a[0];        a_old[1] = a[1];        //计算每个样本分别被两个模型抽中的概率        vector<FLOAT2> px;            vector<EMData>::iterator it;        for(it = Data.begin(); it < Data.end(); it++)        {            FLOAT2 p;            p.f1 = 1/(sqrt(2 * PI * sex[0].var)) * exp(-(it->fHeight - sex[0].mean) * (it->fHeight - sex[0].mean) / (2 * sex[0].var));            p.f2 = 1/(sqrt(2 * PI * sex[1].var)) * exp(-(it->fHeight - sex[1].mean) * (it->fHeight - sex[1].mean) / (2 * sex[1].var));            px.push_back(p);        }        //E步        //计算每个样本属于男生或女生的概率        vector<FLOAT2>::iterator it2;        for(it2 = px.begin(); it2 < px.end(); it2++)        {            float sum = 0.0;            (*it2).f1 *= a[0];            sum += (*it2).f1;            (*it2).f2 *= a[1];            sum += (*it2).f2;            (*it2).f1 = (*it2).f1/sum;            (*it2).f2 = (*it2).f2/sum;        }        //M步        float sum_male = 0, sum_female = 0;        float sum_mean_male = 0, sum_mean_female = 0;        for(it2 = px.begin(), it = Data.begin(); it2 < px.end(); it2++, it++)        {            sum_male += (*it2).f1;            sum_female += (*it2).f2;            sum_mean_male += (*it2).f1 * (it->fHeight);            sum_mean_female += (*it2).f2 * (it->fHeight);        }        //更新a        a[0] = sum_male/(sum_male + sum_female);        a[1] = sum_female/(sum_male + sum_female);        //更新均值        sex[0].mean = sum_mean_male/ sum_male;        sex[1].mean = sum_mean_female/ sum_female;        //更新方差        float sum_var_male = 0, sum_var_female = 0;        for(it2 = px.begin(), it = Data.begin(); it2 < px.end(); it2++, it++)        {            sum_var_male += (*it2).f1 * ((it->fHeight) - sex[0].mean) * ((it->fHeight) - sex[0].mean);            sum_var_female += (*it2).f2 * ((it->fHeight) - sex[1].mean) * ((it->fHeight) - sex[1].mean);        }        sex[0].var = sum_var_male / sum_male;        sex[1].var = sum_var_female / sum_female;        //计算变化率        t = max((a[0] - a_old[0])/a_old[0], (a[1] - a_old[1])/a_old[1]);        t = max(t, (sex[0].mean - sex_old[0].mean)/sex_old[0].mean);        t = max(t, (sex[1].mean - sex_old[1].mean)/sex_old[1].mean);        t = max(t, (sex[0].var - sex_old[0].var)/sex_old[0].var);        t = max(t, (sex[1].var - sex_old[1].var)/sex_old[1].var);    }    //计算正确率    int correct_num = 0;    float correct_rate = 0;    vector<EMData>::iterator it;    for(it = Data.begin(); it < Data.end(); it++)    {        float p[2];        char csex;        for(int i = 0; i < 2; i++)        {            p[i] = 1/(sqrt(2 * PI * sex[i].var)) * exp(-(it->fHeight - sex[i].mean) * (it->fHeight - sex[i].mean) / (2 * sex[i].var));        }        csex = (p[0] > p[1]) ? ‘m‘ : ‘f‘;        if(csex == it->sex)            correct_num++;    }    correct_rate = (float)correct_num / Data.size();    return correct_rate;}int main(){    vector<EMData> Data;    getdata(Data);    float correct_rate = predict(Data);    cout << "correct rate = "<< correct_rate << endl;    return 0;}

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