#P4538.第2题-基于混淆矩阵，推导分类模型的核心评估指标

第2题-基于混淆矩阵，推导分类模型的核心评估指标 - problem_ide - CodeFun2000

import sys
import numpy as np

def solve():
    pred = list(map(int,input().split()))
    trueY = list(map(int,input().split()))
    weights = list(map(float,input().split()))

    n = len(weights)
    m = len(pred)
    #print(n)
    #print(m)
    precision = [0 for _ in range(n)]
    recall = [0 for _ in range(n)]
    f1 = [0 for _ in range(n)]

    for i in range(n):
        TP = 0
        FP = 0
        FN = 0
        
        for j in range(m):
            if(trueY[j]==i or pred[j]==i):
                if(pred[j] == trueY[j]):
                    TP +=1
                elif(pred[j]==i and trueY[j]!=i):
                    FP+=1
                elif(pred[j]!=i and trueY[j]==i):
                    FN+=1
        
        if((TP+FP)!=0):
            precision[i] = TP/(TP+FP)
        else:
            precision[i] = 0
        
        if((TP+FN)!=0):
            recall[i] = TP/(TP+FN)
        else:
            recall[i] = 0
        

        if((precision[i]!=0) and (recall[i]!=0)):
            f1[i] = 2*precision[i]*recall[i]/(precision[i]+recall[i])
        else:
            f1[i] = 0
    
    precision = np.array(precision)
    recall = np.array(recall)
    f1 = np.array(f1)
    #print(precision)
    #print(recall)
    #print(f1)
    
    precision_avg = np.sum(precision*weights)
    recall_avg = np.sum(recall*weights)
    f1_avg = np.sum(f1*weights)

    print(f"{precision_avg:.2f} {recall_avg:.2f} {f1_avg:.2f}",end='')

if __name__ =='__main__':
    solve()