第2题-基于混淆矩阵推导分类模型的核心评估指标 - problem_ide - CodeFun2000import 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): FP1 elif(pred[j]!i and trueY[j]i): FN1 if((TPFP)!0): precision[i] TP/(TPFP) else: precision[i] 0 if((TPFN)!0): recall[i] TP/(TPFN) 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()