\"Machine Intelligence is the last invention that humanity will ever need to make.\"\n- Nick Bostrom
\n\nAnd isn't that the final destination - the ultimate creation to revolutionize our existence? Valued at over 4.6 billion dollars, machine learning and artificial intelligence are just the scratched surface of an untouched mound of treasure.
\n\nAaruush'20 brings to you the “Machine Learning Challenge”, a 40-hour long contest that brings the participants in touch with one of the fastest-growing industries in today's market.
\n\nThe aim of this contest is to expose young learners and aspirants to the fields of data science, machine learning and artificial intelligence. Restating its position as one of the best techno-management collegiate fests of the country, Aaruush provides a platform for the creators of tomorrow to stoke their flames of interest and innovation.
\n\nProblem statement 2:
\nHeart disease classifier
\nGiven 13 features related to heart diseases classify if a patient has heart disease or not.
\n\nFeatures are
\nage
\nsex
\nchest pain type (4 values)
\nresting blood pressure
\nserum cholestoral in mg/dl
\nfasting blood sugar > 120 mg/dl
\nresting electrocardiographic results (values 0,1,2)
\nmaximum heart rate achieved
\nexercise induced angina
\noldpeak = ST depression induced by exercise relative to rest
\nthe slope of the peak exercise ST segment
\nnumber of major vessels (0-3) colored by flourosopy
\nthal: 3 = normal; 6 = fixed defect; 7 = reversable defect
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"name": "Description",
"content": "\"Machine Intelligence is the last invention that humanity will ever need to make.\" - Nick Bostrom\nAnd isn't that the final destination - the ultimate creation to revolutionize our existence? Valued at over 4.6 billion dollars, machine learning and artificial intelligence are just the scratched surface of an untouched mound of treasure.\nAaruush'20 brings to you the “Machine Learning Challenge”, a 40-hour long contest that brings the participants in touch with one of the fastest-growing industries in today's market.\nThe aim of this contest is to expose young learners and aspirants to the fields of data science, machine learning, and artificial intelligence. Restating its position as one of the best techno-management collegiate fests of the country, Aaruush provides a platform for the creators of tomorrow to stoke their flames of interest and innovation.\nThe participants will experiment with different techniques and compete against each other to produce the best models on the given problem statements and datasets.\nThis contest not only gives the participants a splendid opportunity of experiencing the applications of Machine Learning in real-life problems but also leave with a handful of goodies and incentives.\nSo what are you waiting for? Join the ML uprising!\n\n**Problem statement**:\nHeart disease classifier \nGiven 13 features related to heart diseases classify if a patient has heart disease or not",
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"name": "Evaluation",
"content": "
The evaluation pages describes how submissions will be scored and how students should format their submissions. You don't need a sub-title at the top (the page title appears above). For an example of a high quality evaluation page, see the 2013 KDD Cup page, which we have copied here:
\nThe evaluation metric for this competition is Mean F1-Score. The F1 score, commonly used in information retrieval, measures accuracy using the statistics precision p and recall r. Precision is the ratio of true positives (tp) to all predicted positives (tp + fp). Recall is the ratio of true positives to all actual positives (tp + fn). The F1 score is given by:
\n\\[ F1 = 2\\frac{p \\cdot r}{p+r}\\ \\ \\mathrm{where}\\ \\ p = \\frac{tp}{tp+fp},\\ \\ r = \\frac{tp}{tp+fn} \\]
\nThe F1 metric weights recall and precision equally, and a good retrieval algorithm will maximize both precision and recall simultaneously. Thus, moderately good performance on both will be favored over extremely good performance on one and poor performance on the other.
\nFor every author in the dataset, submission files should contain two columns: AuthorId and DuplicateAuthorIds. DuplicateAuthorIds should be a space-delimited list. Every AuthorId counts as his/her own duplicate, and every duplicate should be listed under each of its respective ids. For example, if you suspect author A, B, and C are the same, you should list (A,A B C), (B,B A C), (C,C A B).
\nThe file should contain a header and have the following format:
\nAuthorId,DuplicateAuthorIds", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "rules", "content": "**RULES FOR ML CHALLENGE**\n\n**One account per participant:**\nYou cannot sign up to Kaggle from multiple accounts and therefore you cannot submit from multiple accounts. \n\n**No private sharing outside teams: **\nPrivately sharing code or data outside of teams is not permitted. It's okay to share code if made available to all participants on the forums. \n\n**Competition Entry: **\nNO PURCHASE NECESSARY TO ENTER OR WIN. \nTo enter the Competition, you must register on the Competition website prior to the Entry Deadline, and follow the instructions for developing and entering your Submission through the Competition Website.\n\n**Competition Period:**\nFor the purposes of Prizes, the Competition will run from the Start Date and time to the End Date and time (such duration the “Competition Period”). The Competition timeline is subject to change, and Competition Sponsor may introduce additional hurdle deadlines during the Competition Period. Any updated or additional deadlines will be publicized on the Competition Website. It is your responsibility to check the Competition Website regularly to stay informed of any deadline changes. \n\nYOU ARE RESPONSIBLE FOR DETERMINING THE CORRESPONDING TIME ZONE IN YOUR LOCATION. \n\n**Submission Limits: **\n•\tYou may submit a maximum of 5 submissions per day. \n•\tYou may select up to 2 final submissions for judging. \n\n**Submissions: **\n•\tTo be eligible for scoring and a position on the leader board, your submissions to the Competition (“Submissions”) must be made during the Competition Period, and in compliance with the rules. \n•\tSubmissions may not be accepted or scored if they are in whole or part illegible, incomplete, damaged, altered, counterfeit, obtained through fraud, or late. \n•\tYour Submission must be your own, original work such that you are the sole and exclusive owner and rights holder of the Submission, and that you have the right to make the Submission and grant all required licenses. \n•\tSubmissions may not use or incorporate information from hand labelling or human prediction of the validation dataset or test data records. \n•\tIf open source code is used in the Submission, then you must only use open source code licensed under an Open Source Initiative-approved license (see www.opensource.org) that in no event limits commercial use of such code or model containing or depending on such code. \n•\tYour Submissions must be made in the manner and format, and in compliance with all other requirements, stated on the Competition Website (the \"Requirements\"). Submissions must be received before any Submission deadlines stated on the Competition Website. \n\n**Competition Data: **\n\"Competition Data\" means the data or datasets available from the Competition Website for the purpose of use in the Competition, including any prototype or executable code provided on the Competition Website. The Competition Data will contain private and public test sets. Which data belongs to which set will not be made available to participants. \nA.\tData Access and Use. You may access and use the Competition Data for any purpose, whether commercial or non-commercial, including for participating in the Competition and on Kaggle.com forums, and for academic research and education. The Competition Sponsor reserves the right to disqualify any participant who uses the Competition Data other than as permitted by the Competition Website and these Rules. \nB.\tData Security. You agree to use reasonable and suitable measures to prevent persons who have not formally agreed to these Rules from gaining access to the Competition Data. You agree not to transmit, duplicate, publish, redistribute or otherwise provide or make available the Competition Data to any party not participating in the Competition. You agree to notify Kaggle immediately upon learning of any possible unauthorized transmission of or unauthorized access to the Competition Data and agree to work with Kaggle to rectify any unauthorized transmission or access. \n\n**Disqualification:** \nKaggle may disqualify any participant from the competition if Kaggle reasonably believes that the participant has attempted to undermine the legitimate operation of the Competition, for example, by cheating, violating the rules, tampering with the submission process or any other part of the competition or competition Website, other unfair practices or abuses, or threatens or harasses any other participants or Kaggle.\n\n**Team Aaruush** can also disqualify people on grounds of unethical conduct or tampering with the final or Intermediate Submissions in any form.\n A disqualified participant may be removed from the Competition leader board, at Kaggle’s or Team Aaruush’s discretion.\n\n\n**Please find the Terms and Conditions of the competition** [here](https://drive.google.com/file/d/1i0dxKLeI29KnyhJrz6BF5BFOKocSVwzH/view?usp=sharing)", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Timeline", "content": "**Start of the Challenge** - 09/10/2020, 8:00AM\n**End of the Challenge** - 10/10/2020, 11:59PM\n\nNOTE: The timings mentioned above are as per IST. The competition organizers reserve the right to update the contest timeline if they deem it necessary.", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Prizes And Incentives", "content": "**Winners**\nPrizes worth up to 15k.\nFree online courses and online internship opportunities to the winners!\nCertificate of appreciation.\n\n**Certificate of Participation** will be provided to all the participants", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false } ] }
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