C++로 만드는 perceptron

학교 과제에서 perceptron 구현하는게 있었는데 그냥 올려본당

Class0 = {0.05, 0.1, 0.15, 0.2, 0.05, 0.3, 0.35, 0.4, 0.45, 0.49, 0.52, 0.56, 0.57, 0.82}

Class1 = {0.12, 0.47, 0.48, 0.5, 0.55, 0.6, 0.65, 0.7, 0.75, 0.8, 0.85, 0.9, 0.95} 

#include<iostream>
#include <vector>
using namespace std;
 
float w0 = -0.1;
float w1 = -0.36;
float learning_rate = 0.1;
 
 
void perceptron(vector<float> class0, vector<float> class1){
    int misclassified_num = 0;
    float learning_num = 0;
    cout << "(w0 : " << w0 << ", w1 : " << w1 << ")" << endl;
 
    for (int i = 0; i < class0.size(); i++){
        if (w0 * class0[i] > 0){
            misclassified_num++;
            learning_num = class0[i];
        }
    }
    w0 = w0 + (learning_rate*learning_num);
 
    for (int i = 0; i < class1.size(); i++){
        if (w1 * class1[i] < 0){
            misclassified_num++;
            learning_num = class1[i];
        }
    }
    w1 = w1 + (learning_rate*learning_num);
 
    cout << "misclassified_num : "<< misclassified_num << endl << endl;
 
    if (misclassified_num != 0){
        perceptron(class0, class1);
    }
    else{
        cout << w0 << "," << w1 << endl;
    }
}
 
 
int main(){
    vector<float> input_class0;
    vector<float> input_class1;
 
    int data_num = 0;
    float input_data = 0;
 
    cout << "input the number of class0 data : ";
    cin >> data_num;
 
    for (int i = 0; i < data_num; i++){
        cout << "input the data ("<<i<<"): ";
        cin >> input_data;
        input_class0.push_back(input_data);
    }
 
    cout << "input the number of class1 data : ";
    cin >> data_num;
 
    for (int i = 0; i < data_num; i++){
        cout << "input the data (" << i << "): ";
        cin >> input_data;
        input_class1.push_back(input_data);
    }
 
    perceptron(input_class0, input_class1);
 
 
}

input the number of class0 data : 14

input the data (0): 0.05

input the data (1): 0.1

input the data (2): 0.15

input the data (3): 0.2

input the data (4): 0.25

input the data (5): 0.3

input the data (6): 0.35

input the data (7): 0.4

input the data (8): 0.45

input the data (9): 0.49

input the data (10): 0.52

input the data (11): 0.56

input the data (12): 0.57

input the data (13): 0.82

input the number of class1 data : 13

input the data (0): 0.12

input the data (1): 0.47

input the data (2): 0.48

input the data (3): 0.5

input the data (4): 0.55

input the data (5): 0.6

input the data (6): 0.65

input the data (7): 0.7

input the data (8): 0.75

input the data (9): 0.8

input the data (10): 0.85

input the data (11): 0.9

input the data (12): 0.95

(w0 : -0.1, w1 : -0.36)

misclassified_num : 13

(w0 : -0.1, w1 : -0.265)

misclassified_num : 13

(w0 : -0.1, w1 : -0.17)

misclassified_num : 13

(w0 : -0.1, w1 : -0.075)

misclassified_num : 13

(w0 : -0.1, w1 : 0.02)

misclassified_num : 0

-0.1,0.02