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有人了解KDD CUP么？
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今天看上台湾大学的ML课，才知道有KDD CUP : ACM SIGKDD Conference on Knowledge Discovery and Data Mining
往年的题目都很有意思，可以拿到一般接触不到的数据，比如2012年是腾讯赞助的，可以拿到50万用户在某一时段的资料.鐣欏璁哄潧-涓浜-涓夊垎鍦
比赛规格非常高，各种牛校牛公司参加，可惜今年的due已经过了。
不知地里有没了解KDD的人？
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中级农民-加分请看右边栏-多参与|分享|记录|反馈, 积分 393, 距离下一级还需 107 积分
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在这里 的competition里面找KDD，12和13年的比赛都是这里举办的。
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我想知道你到底是研究啥的
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大概沾点边... 台大似乎搞KDD cup搞的很强力来着...
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KDD 是一个大的话题 里面有很多技术，理论，还有经验
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我想知道你到底是研究啥的
Eroica是全能型选手，对计算机和统计都有相当好奇心的good learner, good teacher~
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屌丝队KDD CUP的经历各种膜拜中
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anonym 发表于
我想知道你到底是研究啥的. 鍥磋鎴戜滑@1point 3 acres
码农+统计民工。。随便找些数据玩
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EroicaCMCS 发表于
码农+统计民工。。随便找些数据玩
呸 码农+统计还说自己是民工
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KDD Cup 2015 - Predicting dropouts in MOOC
If you have any questions or comments, please send an email to .&Update, August 4 :Here is the Schedule&of KDD Cup 2015 WorkshopKDD Cup 2015 Workshop Schedule9:00 – 9:30 Opening: Information about the competition and our Sponsor, XuetangX.9:30 – 10:30 Invited Talk: Jacob Spoelstra, Hang Zhang (Microsoft) Solving the KDD Cup 2015 Challenge Using Azure ML.10:30 – 11:00 Coffee Break11:00 – 11:25 10th Prize: Ikki Tanaka and Shunnosuke Ikeda Ensemble of Diverse Gradient Boosting Decision Trees for MOOCs Dropout Prediction.11:25 – 11:50 9th Prize: Chih-Ming Chen, Man-Kwan Shan, Ming-Feng Tsai, Yi-Hsuan Yang, Hsin-Ping Chen, Pei-Wen Yeh, and Sin-Ya Peng A Linear Ensemble of Classification Models with Novel Backward Cumulative Features for MOOC Dropout Prediction.11:50 – 12:15 7th Prize: Nguyen Minh Luan Combining Intention and Engagement Features with Ensemble of Models for MOOC Dropout Prediction.12:15 – 13:45 Lunch (on your own)13:45 – 14:10 6th Prize: Aakansh Gupta, Nuo Zhang, Kei Yonekawa, Kazunori Matsumoto, Shigeki Muramatsu, Rui Kimura, Nobuyuki Maita, Yujin Tang, Keiichi Kuroyanagi, Takafumi Watanabe, Akihiro Kobayashi, and Takuya Akiyama Approach to Generate a Vast Variety of Features for Predicting Dropouts in MOOC.14:10 – 14:35 5th Prize: Jingming Liu A Time Series Feature Extractor for Predicting Dropouts in MOOC.14:35 – 15:00 4th Prize: Ming-Lun Cai, Chih-Wei Chang, Liang-Wei Chen, Si-An Chen, Hsien-Chun Chiu, Hong-Min Chu, Yu-Jheng Fang, Yi Huang, Kuan-Hao Huang, Chih-Te Lai, Yi-An Lin, Chieh-En Tsai, Yeh-Wen Tsao, Yu-Lin Tsou, Wei-Cheng Wang, Yu-Ping Wu, Yao-Yuan Yang, Sheng-Chi You, Sz-Han Yu, Hsuan-Tien Lin, and Shou-De Lin NearUniform Aggregation of Gradient Boosting Machines for KDD Cup 2015.15:00 – 15:15 Coffee Break15:15 – 15:40 3rd Prize: Kenny Chua, Xavier Conort, Sergey Yurgenson, and Owen Zhang Featurizing Sequential Data - our Solution with XGboost.15:40 – 16:05 2nd Prize: Yuichi Sugiyama, Kei Harada, Sayaka Yabu, Kazuki Onodera, Yuta Hino, Ryotaro Sano, Natsumi Kokubo, Daisuke Nishikawa, Sampei Nakabayashi, Masaaki Takada, Yasushi Iwata, Shinya Yazawa, Ryo Kato, and Tomomitsu Motohashi Feature Extraction for Predicting Dropouts and Feature Merging Experience with Data Veraci.16:05 – 16:30 1st Prize: Jeong-Yoon Lee, Andreas Toescher, Michael Jahrer, Kohei Ozaki, Mert Bay, Peng Yan, Song Chen, Tam T. Nguyen, and Xiaocong Zhou Three-Stage Ensemble and Feature Engineering for MOOC Dropout Prediction.16:30-17:30 The Serial Winner Panel (stay tuned!)Update, July 19:10 winners are listed , one of the KDD Cup chairs will contact you soon.Update, July 14:The scores on the&&is now correct.Update, July 13:The rank of
is correct, but the scores have some errors. We are fixing it.Top 11 players are as follows. The final result is nearly same with the private rank. We will annouce the final winners today.Rank Team （private score）1 Intercontinental Ensemble （0.0387）2 FEG&NSSOL@DataVeraci（0.3106）（0.8484）4 CLMS（0.283）5 ttllbb（0.7709）6 KDDILABS&Keiku（0.9866）7 FirstTimeEver（0.0947）8 xiaochuan（0.3954）9 Donquote（0.3861）10 NCCU（0.9964）11 kyazuki&DT@Keio univ. Ohmori Lab（0.1961）Update, July 12:The submission is closed. The final results with private scores will be published in several hours.&Update, July 11:The submission will be closed at 11:59PM, July 12, 2015 (UTC).&&Updates:&1) Many people have asked the definition of &dropout&. To better explain the definition, we extracted some information from the log file into a new file named &date.csv&. However, all information regarding the data used for this competition has not been changed. So you do not need to change your existing code of algorithms. You can find the details of the file on &data& web page:&&.The sole purpose of creating this new file is to help you understand the definition of dropout. In brief, the timespan of each course is varied, thus the timespan for calculating dropouts depends on the course. We provide the timespan data of each course in date.csv. In addition, the timespan for calculating each course dropout is 10 days after the last day of that course. Please refer to the description of date.csv for more information about dropouts.2) Because of this, we made a decision to extend the deadline of the competition to July 12, so everyone can refer to date.csv. Accordingly, we also shorten the time between the competition end date and the date of announcement, which is also July 12&now.3) Microsoft generously provides their Azure Machine Learning services for KDD Cup participants.&Please find the
here on “Solving the KDD Cup 2015 Challenge Using Azure ML” . This blog provides detailed instruction on how to solve the KDD Cup challenge using Azure ML and achieve an accuracy of 0.87 AUC. This will help participants with a starting point for competing for the KDD Cup and help build even more accurate solutions on top.&For participants who are new to Azure ML, it is a cloud platform for developing machine learning based predictive solutions . It provides a rich UI and battle tested algorithms from Bing and Microsoft Research along with support for R & Python. It also allows users to quickly operationalize their solutions as a webservice.
Background:&Students&#39; high dropout rate on MOOC platforms has been heavily criticized, and predicting their likelihood of dropout would be useful for maintaining and encouraging students&#39; learning activities. Therefore, in KDD Cup 2015, we will predict dropout on XuetangX, one of the largest MOOC platforms in China. &Description：The competition participants need to predict whether a user will drop a course within next 10 days based on his or her prior activities. If a user C leaves no records for course C &in the log during the next 10 days, we define it as dropout from course C For more details about log, please refer to the .&About XuetangX:&, a Chinese MOOC learning platform initiated by Tsinghua University, was officially launched online on Oct 10th, 2013. In April 2014, XuetangX signed a contract with edX, one of the biggest global MOOC learning platform co-founded by Harvard University and MIT, to acquire the exclusive authorization of edX’s high-quality international courses. In December 2014, XuetangX signed the Memorandum of Cooperation with FUN, the national MOOC platform in France, to make bilateral effort in course construction, platform development and other aspects. So far, there are more than 100 Chinese courses and over 260 international courses available on XuetangX.
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The&18th ACM SIGKDD conference on knowledge discovery and data mining will be held in Beijing, China, from August 12-16, 2012.
Aug 12-16, 2012
KDD-2012 Conference
Jun 29, 2012
Early Registration
Jun 29, 2012
KDD Cup Competition Ends
Jun 15, 2012
Workshop Proceedings
May 30, 2012
Deadline for Camera-Ready Submissions
May 11, 2012
Demonstration Notification
May 4, 2012
Paper Acceptance
Apr 6, 2012
Tutorial/Panel Notification
Apr 6, 2012
Demonstration Submission Deadline
Mar 12, 2012
KDD Cup Competition Begins
Mar 5, 2012
Notification of Workshop Decisions
Mar 5, 2012
KDD Cup Registration Opens
Feb 24, 2012
Tutorial/Panel Proposals
Feb 10, 2012*
Paper Submission Deadline
Jan 15, 2012
Workshop Proposal Deadline
Nov 15, 2011**
KDD CUP Proposal Deadline
*Note that there will be no abstract submission deadline, and the paper submission deadline is Feb 10, 2012.
**We start accepting KDD CUP proposals now, but will start making decisions on a first-come-first-serve basis on Nov 15, 2011. Any initial indications are welcome via an informal email to the KDD CUP chairs ().
***All deadlines are for 11:59 PM Pacific time.