From 66ea00a7def21d437ae62ea85259d5881e46574e Mon Sep 17 00:00:00 2001 From: hjm <63528605@qq.com> Date: Tue, 25 Jun 2019 15:02:45 +0800 Subject: [PATCH] test --- public/react/src/context/TPIContextProvider.js | 3 +++ 1 file changed, 3 insertions(+) diff --git a/public/react/src/context/TPIContextProvider.js b/public/react/src/context/TPIContextProvider.js index 6db04f1b8..0b764202f 100644 --- a/public/react/src/context/TPIContextProvider.js +++ b/public/react/src/context/TPIContextProvider.js @@ -516,6 +516,9 @@ pop_box_new(htmlvalue, 480, 182); // test // var data = {"st":0,"discusses_count":12,"game_count":6,"record_onsume_time":5.303,"prev_game":"q67plhfjaogy","next_game":"lfrwm2ohiate","praise_count":0,"user_praise":false,"time_limit":180,"tomcat_url":"http://47.98.226.234","is_teacher":true,"myshixun_manager":false,"game":{"id":1964918,"myshixun_id":510423,"user_id":73892,"created_at":"2019-06-24T11:22:58.000+08:00","updated_at":"2019-06-25T11:15:48.000+08:00","status":0,"final_score":0,"challenge_id":573,"open_time":"2019-06-24T11:22:58.000+08:00","identifier":"yrsxolqk6zcp","answer_open":0,"end_time":null,"retry_status":0,"resubmit_identifier":null,"test_sets_view":false,"picture_path":null,"accuracy":null,"modify_time":null,"star":0,"cost_time":3966,"evaluate_count":1,"answer_deduction":0},"challenge":{"id":573,"shixun_id":186,"subject":"应用模型做预测","position":4,"task_pass":"####本关任务\r\n本关卡学习如何应用机器学习模型来做预测。\r\n\r\n####相关知识\r\n在前一关卡中，我们一起探讨了机器学习的一般原理，并建立了一个非常简单的电影评分模型Model 0：\r\n\r\n评分 = **大众对电影的平均评分** + **用户个人的给分偏好** + **电影的评分偏好**\r\n\r\n针对这个模型，我们设计了一个非常朴素的预测模型Baseline，直接从数据集中统计得到上述三个参数的值。\r\n\r\n在本关卡中，我们将应用这个模型对用户和电影的评分做出预测。\r\n\r\n####编程要求\r\n回顾Model 0的预测评分公式：\r\n```latex\r\nf(u,m)=g+\\alpha(u)+\\beta(m)\r\n```\r\n\r\n我们的Baseline模型得到了$$g$$、$$\\alpha$$和$$\\beta$$三种参数，下面我们实现predict函数，来对测试数据集中未知的用户电影评分进行预测，需要填充的代码块如下：\r\n```python\r\n# -*- coding:utf-8 -*-\r\n\r\ndef predict(g, alpha, beta, test_data):\r\n\t\"\"\"预测用户对电影的评分\r\n\t参数:\r\n\t\tg - 浮点数，模型参数平均电影评分\r\n\t\talpha - 浮点数组，用户评分偏差参数数组\r\n\t\tbeta - 浮点数组，电影评分偏差参数数组\r\n\t\ttest_data - Pandas的DataFrame对象，有两列'user','movie'，是测试数据集\r\n\t返回值：\r\n\t\tret - 浮点数数组，预测的评分数组，举例ret[10]，表示第10组用户和电影对的评分值\r\n\t\"\"\"\t\r\n\tret = []\r\n\tN = len(alpha)\r\n\tM = len(beta)\r\n\t\r\n\t# 请在此添加实现代码\r\n\t#********** Begin *********#\r\n\t\r\n\t#********** End *********#\r\n\t\r\n\treturn ret\r\n```\r\n\r\n####本关任务\r\n本关卡的测试数据来自内置测试文件，平台将比对您所编写函数的预测评分与正确评分，只有所有数据全部计算正确才能进入下一关。","score":500,"path":"src/step4/doprediction.py","st":0,"web_route":null,"modify_time":null},"shixun":{"id":186,"name":"理解机器学习基本概念：从电影评分预测讲起","user_id":24758,"gpid":3676,"visits":622,"created_at":"2017-08-25T18:07:41.000+08:00","updated_at":"2019-06-02T11:05:20.000+08:00","status":2,"language":"MachineLearning","authentication":false,"identifier":"58DRWG63","trainee":3,"major_id":635,"webssh":0,"homepage_show":false,"hidden":false,"fork_from":null,"can_copy":true,"modify_time":"2017-09-29T21:42:16.000+08:00","reset_time":"2017-09-29T21:42:16.000+08:00","publish_time":"2017-09-29T10:58:13.000+08:00","closer_id":null,"end_time":null,"git_url":"educoder/58drwg63","vnc":false,"myshixuns_count":318,"challenges_count":6,"use_scope":0,"mirror_script_id":0,"image_text":null,"code_hidden":false,"task_pass":false,"exec_time":180,"test_set_permission":true,"sigle_training":false,"hide_code":false,"multi_webssh":false,"excute_time":null,"repo_name":"educoder/58drwg63","averge_star":4.9,"opening_time":null,"users_count":10,"forbid_copy":false,"pod_life":0},"myshixun":{"id":510423,"shixun_id":186,"is_public":true,"user_id":73892,"gpid":null,"created_at":"2019-06-24T11:22:55.000+08:00","updated_at":"2019-06-24T13:56:40.000+08:00","status":0,"identifier":"7pkwxim9eh","commit_id":"ff7c6652fdfdf62eaa1316d39400ebdbd6cb81fb","modify_time":"2017-09-29T21:42:16.000+08:00","reset_time":"2017-09-29T21:42:16.000+08:00","system_tip":false,"git_url":null,"onclick_time":"2019-06-24T11:22:55.000+08:00","repo_name":"p35840769/7pkwxim9eh20190624112255"},"user":{"user_id":73892,"login":"p35840769","name":"韩半安","grade":6895,"image_url":"avatars/User/b","school":"国防科技大学","identity":6},"tpm_modified":false,"tpm_cases_modified":false,"mirror_name":["MachineLearning"],"has_answer":true,"test_sets":[{"is_public":true,"result":false,"input":"771 253 360 99 8 759 976 387 873 829 437 53 854 148 447 179 246 810 158 653 583 929 691 892 263 230 637 221 7 652 127 965 767","output":"3.577 -0.329 2.648 4.727 4.351 2.616 3.496 3.059 3.470 3.166 3.064 2.716 3.712 4.003 3.064 3.462 4.004 2.067 3.860 0.121 3.807 3.735 4.230 3.137 4.431 2.468 4.018 5.218 4.351 4.121 4.050 4.587 3.777","actual_output":"Traceback (most recent call last):\r\n File \"src/step4/main.py\", line 3, in \u003cmodule\u003e\r\n from doprediction import predict\r\nImportError: cannot import name 'predict'\r\n","compile_success":1},{"is_public":false,"result":false,"compile_success":1}],"allowed_unlock":true,"last_compile_output":"共有2组测试集，其中有2组测试结果不匹配。详情如下：","test_sets_count":2,"sets_error_count":2} + // data.shixun.vnc = true + // data.vnc_url= "http://47.96.157.89:54144/vnc_lite.html?password=headless" + // this._handleResponseData(data) // return