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      "content": "<p>Please refer to the README.doc file for more information.</p>\r\n<h2>File descriptions</h2>\r\n<ul>\r\n<li><strong>sat-train.libsvm.tr.dat</strong> - libsvm format training file</li>\r\n<li><b>sat-test.csv.dat </b>- the test set in csv format</li>\r\n<li><strong>README.doc</strong>- supplemental information about the data</li>\r\n</ul>",
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      "content": "<p>In information security domain, anomaly detection gains its own importance from researchers day by day. It is discovered that occasionally emerged frauds or intrusions in modern information systems have incurred significant loss when the suspicious activities were not detected or inefficiently processed. Therefore, numerous efforts have been devoted to devise effective detection methods, and then proceed to automation of anomaly identification in real time.</p>\r\n<p>In this practical course, we challenge students with a set of well designated learning tasks, which require the participants to understand the task scenario entirely and to design their own algorithms to identify corresponding anomalies.</p>\r\n<p>The competition on discovering the anomalies will be conducted based on the performance of their algorithms.</p>\r\n<h2>Contacts</h2>\r\n<p>Department of computer science, <a href=\"http://www.sec.in.tum.de\" target=\"_blank\">Chair of IT Security</a></p>\r\n<p>See details in Homepage <a href=\"ml.sec.in.tum.de/adcg\" target=\"_blank\">ADCG SS'14</a></p>\r\n<h2>Acknowledgements</h2>\r\n<p>We thank <a href=\"http://www.sec.in.tum.de/claudia-eckert/\" target=\"_blank\">Prof.Dr.Claudia Eckert</a> for supporting us on this practical course.</p>",
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      "name": "Evaluation",
      "content": "<p>In this challenge, we decided to use the evaluation metrics of accuracy, which maps to the ratio of corrected predicted labels in the whole testing set. Minimal value is 0 indicating a completely wrong answer, whereas 1 indicating a 100% correct answer.</p>\r\n<p>Submission Format</p>\r\n<p>For every team in the dataset, submission files should contain two columns: SampleId and Predicted Label.</p>\r\n<p>The file should contain a header and have the following format:</p>\r\n<pre>Id,Prediction<br />1,2<br />2,3<br />3,1<br />4,7<br />etc.</pre>",
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      "name": "rules",
      "content": "\r\n\t<!-- Begin Base Rules -->\r\n    <h3>One account per participant</h3>\r\n    <p>You cannot sign up to Kaggle from multiple accounts and therefore you cannot submit from multiple accounts.</p>\r\n    <h3>No private sharing outside teams</h3>\r\n    <p>\r\n        Privately sharing code or data outside of teams is not permitted.\r\n        It's okay to share code if made available to all participants on the forums.\r\n    </p>\r\n    <h3>Team Mergers</h3>\r\n    <p>Team mergers are not allowed in this competition.</p>\r\n\r\n    <h3>Team Limits</h3>\r\n    <p>The maximum size of a team is 2 participants.</p>\r\n    <h3>Submission Limits</h3>\r\n    <p>You may submit a maximum of 5 entries per day.</p>\r\n    <p>You may select up to 2 final submissions for judging.</p>\r\n    <h3>Competition Timeline</h3>\r\n    <p>Start Date: <strong>5/11/2014 10:45 PM UTC</strong></p>\r\n    <p>Merger Deadline: <strong>None</strong></p>\r\n    <p>Entry Deadline: <strong>None</strong></p>\r\n    <p>End Date: <strong>5/26/2014 11:59 PM UTC</strong></p>\r\n\t<!-- End Base Rules -->\r\n<p><strong>Visibility</strong></p>\r\n<p>The competition is opened to public, although the general purpose is subject to a practical course hosted in Technische Universität München. All registered students are ought to submit their results online.</p>\r\n<p>What is the team size?</p>\r\n<p>The team can be formed up to two registered students.</p>\r\n<p><strong>What are the credits?</strong></p>\r\n<p>Only registered students in TUM can get credits in the end of competition. Non-participants of the practical course can as well get ranked by uploading results, if they are interested.</p>\r\n<p><strong>How are the credits are evaluated?</strong></p>\r\n<p>Participants (registered students) are required to take part in each session in class. They ought to present their results in public and also hand in a short report (maximal 2 pages). Credits are evaluated based on their performance and also the results.</p>\r\n<p><strong>How to avoid cheating?</strong></p>\r\n<p>Teams are required to complete the challenges individually. If teams present similar reports/results, they are forced to proceed to a check-phase to defend themselves.</p>",
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