#!/usr/bin/env python# -*- coding: utf-8 -*-""" @File : recall.py @Author : 郭凯锋 @Time : 2020/1/12 17:57 @Software : PyCharm @Git-Hub : daguonice @博客园: https://www.cnblogs.com/daguonice/ """import pandas as pdimport numpy as npfrom sklearn.metrics import recall_scoredef right_or_wrong(ypred_ele, ytrue_ele): if ypred_ele in ytrue_ele: return True else: return Falsedef get_single_score(y_true, y_pred): TP = np.sum(np.logical_and(np.equal(y_true, 1), np.equal(y_pred, 1))) FP = np.sum(np.logical_and(np.equal(y_true, 0), np.equal(y_pred, 1))) TN = np.sum(np.logical_and(np.equal(y_true, 1), np.equal(y_pred, 0))) FN = np.sum(np.logical_and(np.equal(y_true, 0), np.equal(y_pred, 0))) recall = [TP, (TP + FN)] accuracy = [(TP + TN), len(y_pred)] return accuracy, recalldef get_multi_score(y_true, y_pred): list_score = [] for ele in ['相互宝', '健康险', '保险线', '花呗']: y_true_temp = np.zeros(len(y_true)) y_pred_temp = np.zeros(len(y_pred)) for idx in range(len(y_true)): if y_pred[idx] == ele: y_pred_temp[idx] = 1. if right_or_wrong(ele, y_true[idx]): y_true_temp[idx] = 1. accuracy, recall = get_single_score(y_true_temp, y_pred_temp) # 变成百分制 list_score.append([accuracy, recall]) return list_score # 返回一个三维列表， 分别是相互宝、健康险、保险线的准确率和召回率的分数def fraction2decimal(result): res = [] for ele in result: list_ele = [] for lab in ele: list_lab = [] for score in lab: if score[1] == 0: list_lab.append(0.0) else: list_lab.append(round(score[0] / score[1], 2)) list_ele.append(list_lab) res.append(list_ele) return resdef func(y_true, y_pred): # y_true是一个一维列表， y_pred是一个二维列表 if len(y_true) != len(y_pred): raise Exception("The two input lengths are inconsistent") length = len(y_true) list_score = get_multi_score(y_true, y_pred) result = [] temp_list = list_score for idx in range(length): list_score = temp_list if len(y_true[idx]) == 1 and y_pred[idx] not in y_true[idx]: list_score[1][1][1] += 1 list_score[0][0][1] += 1 result.append(list_score) elif len(y_true[idx]) == 2 and y_pred[idx] in y_true[idx]: list_score[0][0][0] += 1 list_score[0][0][1] += 1 list_score[0][1][0] += 1 list_score[0][1][1] += 1 result.append(list_score) elif len(y_true[idx]) == 2 and y_pred[idx] not in y_true[idx]: list_score[1][1][1] += 1 list_score[2][1][1] += 1 list_score[0][0][1] += 1 result.append(list_score) else: result.append(list_score) result = fraction2decimal(result) return resultif __name__ == '__main__': alist = ['相互宝', '相互宝', '相互宝', '健康险', '保险线', '花呗'] blist = ['健康险', ['健康险', '相互宝'], ['健康险', '保险线'], ['相互宝'], ['保险线'], ['花呗']] res = func(blist, alist) # res = pd.DataFrame(res, columns=['相互宝', '健康险', '保险线', '花呗']) # pd.set_option('display.max_columns', None) # pd.set_option('display.max_rows', None) # pd.set_option('display.width', 100000) # pd.set_option('display.unicode.east_asian_width', True) print() print(res)
来源：https://www.cnblogs.com/daguonice/p/12185479.html