{ "fetched_at": "2026-10-19T08:21:53Z", "source_url": "https://www.kaggle.com/competitions/emsi-5iir-ds/data", "pages": [ { "name": "rules", "content": "### One account per participant\n \nYou cannot sign up to Kaggle from multiple accounts and therefore you cannot submit from multiple accounts.\n\nYour account must have your entire name and group.\n \n### No private sharing outside teams\n \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### Team Limits\n \nThe maximum team size is 3.\n \n### Submission Limits\n \nYou may submit a maximum of 5 entries per day.\n \nYou may select up to 3 final submissions for judging.\n \n### Competition Timeline\n \nCompetition Timeline dates (including Entry Deadline, Final Submission Deadline, Start Date, and Team Merger Deadline, as applicable) are reflected on the competition’s [Overview > Timeline](https://www.kaggle.com/c/tabular-playground-series-may-2022/overview/timeline) page.\n \n", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Description", "content": "This competition is a clone of the [May edition of the 2022 Tabular Playground series.](https://www.kaggle.com/competitions/tabular-playground-series-may-2022)\nIt is a binary classification problem that includes a number of different feature interactions. This competition is an opportunity to explore various methods for identifying and exploiting these feature interactions.\n\n\n\n## About the Tabular Playground Series\n\nKaggle competitions are incredibly fun and rewarding, but they can also be intimidating for people who are relatively new in their data science journey. In the past, we've launched many Playground competitions that are more approachable than our Featured competitions and thus, more beginner-friendly.\n\nThe goal of these competitions is to provide a fun and approachable-for-anyone tabular dataset to model. These competitions are a great choice for people looking for something in between the Titanic Getting Started competition and the Featured competitions. If you're an established competitions master or grandmaster, these probably won't be much of a challenge for you; thus, we encourage you to avoid saturating the leaderboard.\n\nFor each monthly competition, we'll be offering Kaggle Merchandise for the top three teams. And finally, because we want these competitions to be more about learning, we're limiting team sizes to 3 individuals.\n\n### Getting Started\n \nFor ideas on how to improve your score, check out the [Intro to Machine Learning](https://www.kaggle.com/learn/intro-to-machine-learning) and [Intermediate Machine Learning](https://www.kaggle.com/learn/intermediate-machine-learning) courses on Kaggle Learn.\n\nWe've also built a [starter notebook](https://www.kaggle.com/code/paultimothymooney/getting-started-with-tensorflow-decision-forests) for you that uses TensorFlow Decision Forests, a TensorFlow library that matches the power of XGBoost with a friendly, straightforward user interface.\n \nYou can also read [this blog post](https://towardsdatascience.com/progressively-approaching-kaggle-f58db71a42a9)\n*Good luck, have fun!*", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Evaluation", "content": "Submissions are evaluated on [area under the ROC curve](http://en.wikipedia.org/wiki/Receiver_operating_characteristic) between the predicted probability and the observed target.\n\n\n## Submission File\nFor each `id` in the test set, you must predict a probability for the `target` variable. The file should contain a header and have the following format:\n\n id,target\n 900000,0.65\n 900001,0.97\n 900002,0.02\n etc.\n", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Timeline", "content": "* **Start Date** - December 3, 2022\n* **Entry deadline** - Same as the Final Submission Deadline\n* **Team Merger deadline** - Same as the Final Submission Deadline\n* **Final submission deadline** - January 8, 2023\n\n", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "data-description", "content": "For this challenge, you are given (simulated) manufacturing control data and are tasked to predict whether the machine is in state `0` or state `1`. The data has various feature interactions that may be important in determining the machine state.\n\nGood luck!\n\n## Files\n\n* **train.csv** - the training data, which includes normalized continuous data and categorical data\n* **test.csv** - the test set; your task is to predict binary `target` variable which represents the state of a manufacturing process\n* **sample_submission.csv** - a sample submission file in the correct format", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Prizes", "content": "* 1st Place - **3 points Bonus** on the **Final Exam** + **2 points Bonus** (in this competition) for the entire class of the winner\n* 2nd Place - **2 points Bonus** on the **Final Exam**\n* 3rd Place - **1 point Bonus** on the **Final Exam**\n\n**Please note:**\nPlaces cannot be shared:\n* In the event that several teams have the same ranking, priority will be given to the smallest team. \n* If several teams of the same size have the same ranking, a draw will determine which team will receive the bonus", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false } ] }