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獎項提供單位

MathWorks成立於1984年,致力於工程師與科學家所專用高科技運算分析軟體的開發研究,已在學界、業界奠定領導地位。以 MATLAB & Simulink 為平台,在數學、運算分析、人工智慧,深度/機器學習、預測性維護、控制、數位訊號和5G通訊領域提供了無數的解決方案。至今全球已有超過、百萬以上之客戶,包括:汽車、航太、電信與機器人、政府機構、電子、生化製藥、金融科技以及儀器量測…等產業。

成立於1998年9月,以提供創新、高效率的專業技術支援為經營理念,提供研發導向之專業軟體工具,服務於半導體、機器人/馬達控制、工具機、人工智慧開發、5G無線通訊、無人車自主系統、影像處理、量測、光電、生物科技與財務模型分析等領域之高科技研發人員、科學家與工程師。秉持對客戶的承諾,將不斷地追求創新,以豐富與精深的專業知識,提供客戶具前瞻性的解決方案與設計環境,從研發設計周期之分析、架構、模擬、驗證,乃至HDL驗證、硬體實現之完整解決方案。

2020/11/03 Private Leaderboard調整

經查證,因參賽者資格有疑慮,故重新調整 Private Leaderboard。 報告繳交截止日期延至11月9日,預計11月11日公布得獎名單。

2020/10/27 「挑選成果」功能已開啟,請至上傳頁籤挑選最後成績

請大家至「上傳」→「挑選成果」中選取成績。 可挑選 1~3 筆,系統會以 3 筆中成績最高者作為 private leaderboard 成績。 未選擇最後成績視為棄權,將不會有private leaderboard排名。 請大家記得挑選 祝大家有好成績 謝謝!

Introduction

matlab

Employees are the most important asset of a company. For organizations to make steady growth, it is important to detect early signs of employee turnover and retain top talents. The prediction of employee turnover is based on big data and artificial intelligence to analyze possibilities of resignation. Talent retention initiatives can be activated as soon as possible when warnings are identified.

Many indices of employee turnover are collected, such as age, performance records, highest academic degree, number of business trips and number of leaves, and etc. HR professionals need to evaluate the tendency of employees leaving by referring to past experiences and working conditions. In this topic, participants are asked to build models to predict whether the employee will resign by adopting the method of machine learning.

 

Prize

The following awards will be given to the top three participants on the Private Leaderboard whose score is higher than the baseline 0.18 and the report is submitted before 11/4.

First place: 150,000 discount points of hicloud + NTD 15,000 (Tax included)

Second place: 100,000 discount points of hicloud + NTD 10,000 (Tax included)

Third place: 50,000 discount points of hicloud + NTD 5,000 (Tax included)

Honorable mention: 50,000 discount points of hicloud (multiple winners, depends on the final result)

* Hicloud discount points were provided by Chunghwa Telecom

Notes:
1. Hicloud points can redeem service charge. After the discount, the price will be charged at 30% off based on the list price automatically.

2. Chunghwa Telecom reserves the right to make changes to the terms and conditions herein.

3. The example of discount points calculation can be referred to https://aidea-web.tw/computing


matlab

 

Activity time

The activity time will be based on Taiwan Standard Time (UTC+8), and the schedule is as follows.

TimeEvent
2020/08/05Registration begins
2020/08/19Upload begins
2020/10/28Upload deadline
2020/11/04Report submission deadline
2020/11/11Awards announcement

 

Evaluation Criteria

Evaluations are conducted by calculating the Mean Absolute Error F beta score [1],beta = 1.5

The formula is as follows:

$$ F_{\beta} = {(1+\beta^2)\cdot {precision \cdot recall \over (\beta ^2 \cdot precision)+recall}} \\ $$

Reference
[1] F1 score: https://en.wikipedia.org/wiki/F1_score

Rules

  • The evaluation will be based on the final uploaded result. If multiple participants get the same evaluation scores, the time of uploading will determine the ranking.
  • The maximum number of uploading times is 3 times per day.
  • This issue does not offer a team-up option, only one account per person is allowed and each person can only participate once. If any violations are found, people who are involved would be forced to withdraw the activity.
    When using external data sets, participants should avoid using future data as the basis of the prediction results, and must state source of data sets in the forum for references.
  • All the data, techniques and source codes are original work of participants or are used by permission complying with laws and regulations. If any third-party claims their intellectual property rights or other rights and interests are being violated, the participant will need to handle the disputes personally. If any participants violate intellectual property rights, they will be disqualified, and shall bear legal responsibilities.
  • All the achievements and their IPRs (intellectual property rights) belong to the participants, and the Copyright License Agreements, patent applications, technology transfer and equity distributions of them, should be in accordance with the relevant Laws and Regulations.
  • There should be no answer discussions between different accounts, or it will be considered as cheating.
  • If there is cheating or fraud during the activity, the team that cheats will be disqualified from the activity and the vacancy would be filled up by other teams in the ranking order.
  • After uploading, the answers of test data would be divided into two parts to calculate the score:
    • Before the deadline of the activity: The system refers to only a part of the test data to examine and calculate the score. The result will be posted on the Public Leaderboard as reference for the final score and ranking. This data accounts for 40% of the entire test data.
    • After the deadline of the activity: The system refers to the remaining test data (60%) to examine and calculate the score. The result will be posted on the Private Leaderboard as reference for the final score and ranking.
  • After being notified, finalists need to submit their report before 11/4 to be eligible for the award (the report will not be disclosed or published).
  • Should there be disputes, the organizer reserves the right to make the final decision.