{ "fetched_at": "2026-10-19T09:32:32Z", "source_url": "https://www.kaggle.com/competitions/bci-i-idun-eeg-analysis-challenge/data", "pages": [ { "name": "data-description", "content": "This data includes EEG recordings from 4 subjects (3 train and 1 test subjects) monitored during a night of slip with hand-annotations for sleep-related markers. The task is to predict the markers from the EEG data. \n\nWe provide the **raw**, not organized into epochs, EEG data (`.mat` files) and labels (`.csv`) files for all three test subject, and only the EEG data for the fourth. For convenience, we also provide data organized in **epochs** (30s chunks of data aligned to each event onset with the associated marker; in `.npy` files). Participants are encouraged to use the raw un-cut data, apply their own de-noising and pre-processing steps to it and then organizing the data into epochs for training the models and preparing the submission. This is not a requirement, if preferred the pre-processed data made available here can be used directly. \nWe provide [detailed instructions](https://github.com/BCI-I/BCII-IDUN-Challenge-tutorials) on how to process raw EEG and labels data into epochs. These should be followed closely to ensure that the data is correctly formatted for submission. \n\nMore **details about the files**:\n- `.mat` files: raw EEG data (of shape `1 x n_samples`). One for each subject, 4 in total.\n- `.csv` files: raw marker labels. Columns include `Marker` and `Timestamp_samples`. 3 in total (test subject excluded)\n- `subject_X.npy`: EEG data organized with 30s epochs. Of shape `n_epochs x epoch_length`. (4 in total)\n- `subject_Y.npy`: labels for each epoch. Of shape `n_epochs` with the markers names in it. (3 in total). \n\nThe subjects are: `train=[\"S001\", \"S002\", \"S003\"]` and `test=[\"S004\"]`. \n\nWe provide [detailed code](https://github.com/BCI-I/BCII-IDUN-Challenge-tutorials) to load and processed the raw data into epochs as well as to use epochs for training and evaluating ML models and preparing a submission. ", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Description", "content": "**Dataset Overview**\n\nThe dataset for this competition contains EEG data from **four subjects**, with the following split:\n\n\n**Training Set**: Data from three subjects, includes time-series EEG recordings and corresponding event labels.\n**Test Set**: Data from one subject, includes time-series EEG recordings, but does not include event labels. Event labels for the test subject are *held out* and used to evaluate model quality.\n\n\n**Data Collection**\n\nThe EEG data was collected using the[ IDUN Guardian Earbuds](https://iduntechnologies.com/idun-guardian) (see also this [whitepaper](https://25500273.fs1.hubspotusercontent-eu1.net/hubfs/25500273/Official%20White%20Paper%20Folder/White%20Paper%20IDUN%20Technologies.pdf)), a wearable EEG device with in-ear dry electrodes. Each subject's data includes continuous EEG signals recorded overnight while the subjects slept. The sampling rate of the data is 250 Hz, with filtering applied between 0.75 and 35 Hz (we refer to this as *raw EEG data* despite this filtering - participants are encouraged to explore additional pre-processing steps). \nThe IDUN Guardian Earbuds is a single-channel in-ear EEG device that allows for prolonged monitoring of sleep-related neural activity with minimal disruption for the subjects. For this challenge, a second EEG system, with more recording channels, was used as a ground truth to confirm that events detected in the Guardian signal are correct. We *only* provide data from the IDUN Guardian.\nRecordings were analyzed to manually identify the onset of various sleep and wake related neural activity signals (e.g., around REM sleep onset). \n\n\n**Task Description**\nYou will be provided with EEG data segmented into 30-second epochs. Each epoch is aligned to the onset of one sleep event marker (see below). Your goal is to develop a machine learning model that, given a 30s EEG epoch as input can predict the event marker associated with it. \n\nNote that you're given labels for the three train subjects only. You will need to use these to train an algorithm that can then *transfer* to the test subject, for whom you don't have any supervised data. The aim is to develop models that could work for any new subject without requiring additional training.\n\n*Transfer learning* is a challenging but well-studied topic in machine learning. You can implement some of the algorithms described in the literature or develop your own! There are **7 marker types** so you will need to explore various approaches to multi-class classification while considering data preprocessing strategies for EEG data.\n\n\n**Data Composition**\n\n**Epochs**: Data is segmented into 30-second epochs. Each epoch corresponds to a specific sleep event (if any), such as sleep spindles, K-complexes, or REM sleep. \n**Labels**: Each epoch has a label which indicates the sleep event associated to it. Labels are provided as \"strings\" \nwith the event marker (see below).\n\n**Events (Markers)**\n\nThe seven possible sleep events in the dataset are:\n```text\n SS: Sleep Spindles\n K: K-Complexes\n REM: Rapid Eye Movements\n Son: Sleep Onset\n Soff: Sleep Offset\n A: Arousals\n MS: Microsleep\n```\n\n**Continuous EEG data**: we provide data cut into epochs for convenience. The final submission for this challenge will have to be made using data organized into epochs. However, we also provide the \"un-cut\" data (continuous EEG recording over an entire night and associated markers timestamps). This is intended to be used by participants wishing to apply pre-processing steps to the EEG data that don't work well with data already cut into epochs. We have example code [here](https://github.com/BCI-I/BCII-IDUN-Challenge-tutorials) showing how to organize the continuous EEG data into epochs for fitting ML models and preparing a submission file. \n\n\n**Baseline Models and Code**\n\nTo help participants get started, we provide:\n\n- Starter code for data exploration, preprocessing guidance, and visualization of the class distributions.\n- Baseline models to give you a sense of initial performance, some of the main pitfalls in approaching this challenge and inspire your model development.\n- Detailed instructions on how to prepare and format your submission.\n\nCheck out the example code [here](https://github.com/BCI-I/BCII-IDUN-Challenge-tutorials).\n\nFeel free to experiment with preprocessing techniques, feature extraction, and model optimization to create an effective classification pipeline.\n\n\n\n## Tutorials and other useful materials \n[Competition-specific tutorials](https://github.com/BCI-I/BCII-IDUN-Challenge-tutorials)\n\n- **Useful Resources and Toolboxes**:\n - [MNE Python Library](https://mne.tools/stable/index.html) for comprehensive EEG data analysis tools.\n - [pyRiemann Library](https://pyriemann.readthedocs.io/en/latest/index.html) for covariance matrix manipulation and classification in Riemannian space.\n - [Analysing EEG Data with MNE Tutorial](https://kel-github.github.io/), covering various aspects of EEG processing.\n\n### Tips for success!\n- **Multi-Class Machine Learning Challenge**: Participants will tackle a multi-class classification problem with seven EEG markers, requiring sophisticated strategies for classifying multiple classes effectively.\n- **Class Imbalance**: The dataset presents challenges with class imbalances. Participants will be provided with exploratory code in the 'Exploratory Data Analysis' section to visualize and understand these imbalances, crucial for developing effective models.\n- **Transfer Learning Opportunity**: This competition involves transfer learning, with models trained on data from two subjects and tested on others, simulating real-world scenarios of model generalization.\n- **Challenges of EEG Data Analysis**: EEG data analysis involves handling signal noise, variability, and artifacts. Participants are advised to employ preprocessing methods for data cleaning and enhancement.", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Evaluation", "content": "**Evaluation data**\nEvaluation is performed on data from the test subject. Participants will receive the test subect's EEG data, but not the event labels associated with it. These will have to be predicted from the EEG data **using ML models trained on data from the training subjects**. \n\n```text\n Tip - you'll need to train your models on data from some individuals and apply to data from a new individual that was not part of the training set. Explore different methods to improve your model's ability to transfer to new data. This will be crucial to perform well in the challenge!\n```\n\nLike the training data, the evaluation EEG data includes raw EEG signal organized in 30s epochs. Each epoch is associated with a single event marker, which the models will need to predict.\n\nRefer to the [tutorials](https://github.com/BCI-I/BCII-IDUN-Challenge-tutorials) for more details about the evaluation data, metric and submission file.\n\n\n**Metric**\nGiven the dataset’s class imbalance, this competition uses the Weighted F1-Score as the primary evaluation metric. The Weighted F1-Score emphasizes the importance of both precision and recall across classes, providing a balanced assessment of model performance, especially on underrepresented classes.\n\n## Submission File\nYou will need to provide a submission `.csv` file. We've provided detailed instructions on how to prepare this data in the tutorials linked above. Your submission file should have as many rows as there are epochs in the test dataset. Each row should have an `ID` (the epoch's number in the dataset, starting at 0) and a `TARGET`, a string with the marker's name predicted by your model. \n\n ID,Marker\n 1,REM\n 2,K\n 3,A\n etc...\n\n", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "rules", "content": "##ENTRY IN THIS COMPETITION CONSTITUTES YOUR ACCEPTANCE OF THESE OFFICIAL COMPETITION RULES.\n\n**[See Section 3.18 for defined terms](rules#18.-terms)**\n\n*The Competition named below is a skills-based competition to promote and further the field of data science. You must register via the Competition Website to enter. To enter the Competition, you must agree to these Official Competition Rules, which incorporate by reference the provisions and content of the Competition Website and any Specific Competition Rules herein (collectively, the \"Rules\"). Please read these Rules carefully before entry to ensure you understand and agree. You further agree that Submission in the Competition constitutes agreement to these Rules. You may not submit to the Competition and are not eligible to receive the prizes associated with this Competition unless you agree to these Rules. These Rules form a binding legal agreement between you and the Competition Sponsor with respect to the Competition. Your competition Submissions must conform to the requirements stated on the Competition Website. Your Submissions will be scored based on the evaluation metric described on the Competition Website. Subject to compliance with the Competition Rules, Prizes, if any, will be awarded to Participants with the best scores, based on the merits of the data science models submitted. See below for the complete Competition Rules.*\n\n**You cannot sign up to Kaggle from multiple accounts and therefore you cannot enter or submit from multiple accounts.**\n\n\n#### Competition specific rules\nThis competition is open to everyone, regardless of experience level. Whether you're new to EEG analysis or have expertise in machine learning, you're encouraged to join and explore this unique dataset. There are no cash prizes, but winning teams will have the invaluable opportunity to engage with the IDUN Technologies team, discussing their solutions and gaining insights from experts in neurotechnology.\n\nEach team can have up to six members, so feel free to collaborate and bring together diverse skills. Standard competition rules apply, ensuring fair and respectful participation for everyone. Good luck, and enjoy the challenge!\n\n#### GOVERNING LAW\n\na. Unless otherwise provided in the Competition Specific Rules above, all claims arising out of or relating to these Rules will be governed by California law, excluding its conflict of laws rules, and will be litigated exclusively in the Federal or State courts of Santa Clara County, California, USA. The parties consent to personal jurisdiction in those courts. If any provision of these Rules is held to be invalid or unenforceable, all remaining provisions of the Rules will remain in full force and effect.\n", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "abstract", "content": "Welcome to the BCI Initiative & IDUN competition!\n\nThis challenge invites you to explore the fascinating world of sleep science using real EEG data collected with [IDUN Guardian Earbuds](https://iduntechnologies.com/idun-guardian). The goal is to develop machine learning models that can accurately classify sleep events from EEG data.\n\nSleep analysis offers unique insights into memory, cognition, and health, with broad implications for neuroscience and neurotechnology. In this challenge, you'll receive EEG data from multiple subjects annotated with sleep-related events markers such as sleep spindles, K-complexes, and REM stage. You goal is to develop a machine learning model that can learn to detect these events in the EEG signal, and that can be used to analyze EEG data from new subjects to gain insights into sleep and health. Whether you're a seasoned ML expert or new to EEG analysis, this is a fantastic opportunity to contribute to neurotechnology while building practical skills in EEG data processing and classification. If you're interested in the intersection between machine learning and neurotech, this is the right challenge for you!\n\nRead more about the BCI Initative (https://bci-i.github.io/) and IDUN (https://iduntechnologies.com/)", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "foundational-rules", "content": "The following Kaggle Competition Foundational Rules (“ Foundational Rules ”) apply to every competition regardless of whether the Sponsor creates competition-specific rules. Any competition-specific rules provided by the Sponsor are in addition to these rules, and in the case of any conflict or inconsistency, these Foundational Rules control and nullify contrary competition-specific rules.\n###GENERAL COMPETITION RULES - BINDING AGREEMENT\n####1. ELIGIBILITY\na. To be eligible to enter the Competition, you must be:\n1. a registered account holder at Kaggle.com; \n2. the older of 18 years old or the age of majority in your jurisdiction of residence (unless otherwise agreed to by Competition Sponsor and appropriate parental/guardian consents have been obtained by Competition Sponsor); \n3. not a resident of Crimea, so-called Donetsk People's Republic (DNR) or Luhansk People's Republic (LNR), Cuba, Iran, Syria, or North Korea; and\n4. not a person or representative of an entity under U.S. export controls or sanctions (see: [https://www.treasury.gov/resourcecenter/sanctions/Programs/Pages/Programs.aspx][1]).\n\nb. Competitions are open to residents of the United States and worldwide, except that if you are a resident of Crimea, so-called Donetsk People's Republic (DNR) or Luhansk People's Republic (LNR), Cuba, Iran, Syria, North Korea, or are subject to U.S. export controls or sanctions, you may not enter the Competition. Other local rules and regulations may apply to you, so please check your local laws to ensure that you are eligible to participate in skills-based competitions. The Competition Host reserves the right to forego or award alternative Prizes where needed to comply with local laws. If a winner is located in a country where prizes cannot be awarded, then they are not eligible to receive a prize.\n\nc. If you are entering as a representative of a company, educational institution or other legal entity, or on behalf of your employer, these rules are binding on you, individually, and the entity you represent or where you are an employee. If you are acting within the scope of your employment, or as an agent of another party, you warrant that such party or your employer has full knowledge of your actions and has consented thereto, including your potential receipt of a Prize. You further warrant that your actions do not violate your employer's or entity's policies and procedures. \n\nd. The Competition Sponsor reserves the right to verify eligibility and to adjudicate on any dispute at any time. If you provide any false information relating to the Competition concerning your identity, residency, mailing address, telephone number, email address, ownership of right, or information required for entering the Competition, you may be immediately disqualified from the Competition.\n\n####2. SPONSOR AND HOSTING PLATFORM\n\na. The Competition is sponsored by Competition Sponsor named above. The Competition is hosted on behalf of Competition Sponsor by Kaggle Inc. (\"Kaggle\"). Kaggle is an independent contractor of Competition Sponsor, and is not a party to this or any agreement between you and Competition Sponsor. You understand that Kaggle has no responsibility with respect to selecting the potential Competition winner(s) or awarding any Prizes. Kaggle will perform certain administrative functions relating to hosting the Competition, and you agree to abide by the provisions relating to Kaggle under these Rules. As a Kaggle.com account holder and user of the Kaggle competition platform, remember you have accepted and are subject to the Kaggle Terms of Service at [www.kaggle.com/terms][2] in addition to these Rules.\n\n####3. COMPETITION PERIOD\na. For the purposes of Prizes, the Competition will run from the Start Date and time to the Final Submission Deadline (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. YOU ARE RESPONSIBLE FOR DETERMINING THE CORRESPONDING TIME ZONE IN YOUR LOCATION.\n\n####4. COMPETITION ENTRY\na. NO PURCHASE NECESSARY TO ENTER OR WIN. To 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. Your 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. Submissions not received by the stated deadlines will not be eligible to receive a Prize.\nb. Submissions may not use or incorporate information from hand labeling or human prediction of the validation dataset or test data records.\nc. If the Competition is a multi-stage competition with temporally separate training and/or test data, one or more valid Submissions may be required during each Competition stage in the manner described on the Competition Website in order for the Submissions to be Prize eligible.\nd. Submissions are void if they are in whole or part illegible, incomplete, damaged, altered, counterfeit, obtained through fraud, or late. Competition Sponsor reserves the right to disqualify any entrant who does not follow these Rules, including making a Submission that does not meet the Requirements. \n\n####5. INDIVIDUALS AND TEAMS\na. Individual Account. You may make Submissions only under one, unique Kaggle.com account. You will be disqualified if you make Submissions through more than one Kaggle account, or attempt to falsify an account to act as your proxy. You may submit up to the maximum number of Submissions per day as specified on the Competition Website. \nb. Teams. If permitted under the Competition Website guidelines, multiple individuals may collaborate as a Team; however, you may join or form only one Team. Each Team member must be a single individual with a separate Kaggle account. You must register individually for the Competition before joining a Team. You must confirm your Team membership to make it official by responding to the Team notification message sent to your Kaggle account. Team membership may not exceed the Maximum Team Size stated on the Competition Website.\nc. Team Merger. Teams may request to merge via the Competition Website. Team mergers may be allowed provided that: (i) the combined Team does not exceed the Maximum Team Size; (ii) the number of Submissions made by the merging Teams does not exceed the number of Submissions permissible for one Team at the date of the merger request; (iii) the merger is completed before the earlier of: any merger deadline or the Competition deadline; and (iv) the proposed combined Team otherwise meets all the requirements of these Rules. \nd. Private Sharing. No private sharing outside of Teams. Privately 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####6. SUBMISSION CODE REQUIREMENTS\na. Private Code Sharing. Unless otherwise specifically permitted under the Competition Website or Competition Specific Rules above, during the Competition Period, you are not allowed to privately share source or executable code developed in connection with or based upon the Competition Data or other source or executable code relevant to the Competition (“Competition Code”). This prohibition includes sharing Competition Code between separate Teams, unless a Team merger occurs. Any such sharing of Competition Code is a breach of these Competition Rules and may result in disqualification.\nb. Public Code Sharing. You are permitted to publicly share Competition Code, provided that such public sharing does not violate the intellectual property rights of any third party. If you do choose to share Competition Code or other such code, you are required to share it on Kaggle.com on the discussion forum or notebooks associated specifically with the Competition for the benefit of all competitors. By so sharing, you are deemed to have licensed the shared code under an Open Source Initiative-approved license (see [www.opensource.org][3]) that in no event limits commercial use of such Competition Code or model containing or depending on such Competition Code.\nc. Use of Open Source. Unless otherwise stated in the Specific Competition Rules above, if open source code is used in the model to generate the Submission, then you must only use open source code licensed under an Open Source Initiative-approved license (see [www.opensource.org][4]) that in no event limits commercial use of such code or model containing or depending on such code.\n\n####7. DETERMINING WINNERS\na. Each Submission will be scored and ranked by the evaluation metric stated on the Competition Website. During the Competition Period, the current ranking will be visible on the Competition Website's Public Leaderboard. The potential winner(s) are determined solely by the leaderboard ranking on the Private Leaderboard, subject to compliance with these Rules. The Public Leaderboard will be based on the public test set and the Private Leaderboard will be based on the private test set.\nb. In the event of a tie, the Submission that was entered first to the Competition will be the winner. In the event a potential winner is disqualified for any reason, the Submission that received the next highest score rank will be chosen as the potential winner.\n\n####8. NOTIFICATION OF WINNERS & DISQUALIFICATION\na. The potential winner(s) will be notified by email. \nb. If a potential winner (i) does not respond to the notification attempt within one (1) week from the first notification attempt or (ii) notifies Kaggle within one week after the Final Submission Deadline that the potential winner does not want to be nominated as a winner or does not want to receive a Prize, then, in each case (i) and (ii) such potential winner will not receive any Prize, and an alternate potential winner will be selected from among all eligible entries received based on the Competition’s judging criteria.\nc. In case (i) and (ii) above Kaggle may disqualify the Participant. However, in case (ii) above, if requested by Kaggle, such potential winner may provide code and documentation to verify the Participant’s compliance with these Rules. If the potential winner provides code and documentation to the satisfaction of Kaggle, the Participant will not be disqualified pursuant to this paragraph.\nd. Competition Sponsor reserves the right to disqualify any Participant from the Competition if the Competition Sponsor reasonably believes that the Participant has attempted to undermine the legitimate operation of the Competition by cheating, deception, or other unfair playing practices or abuses, threatens or harasses any other Participants, Competition Sponsor or Kaggle.\ne. A disqualified Participant may be removed from the Competition leaderboard, at Kaggle's sole discretion. If a Participant is removed from the Competition Leaderboard, additional winning features associated with the Kaggle competition platform, for example Kaggle points or medals, may also not be awarded.\nf. The final leaderboard list will be publicly displayed at Kaggle.com. Determinations of Competition Sponsor are final and binding.\n\n####9. PRIZES\na. Prize(s) are as described on the Competition Website and are only available for winning during the time period described on the Competition Website. The odds of winning any Prize depends on the number of eligible Submissions received during the Competition Period and the skill of the Participants. \nb. All Prizes are subject to Competition Sponsor's review and verification of the Participant’s eligibility and compliance with these Rules, and the compliance of the winning Submissions with the Submissions Requirements. In the event that the Submission demonstrates non-compliance with these Competition Rules, Competition Sponsor may at its discretion take either of the following actions: (i) disqualify the Submission(s); or (ii) require the potential winner to remediate within one week after notice all issues identified in the Submission(s) (including, without limitation, the resolution of license conflicts, the fulfillment of all obligations required by software licenses, and the removal of any software that violates the software restrictions).\nc. A potential winner may decline to be nominated as a Competition winner in accordance with Section 3.8.\nd. Potential winners must return all required Prize acceptance documents within two (2) weeks following notification of such required documents, or such potential winner will be deemed to have forfeited the prize and another potential winner will be selected. Prize(s) will be awarded within approximately thirty (30) days after receipt by Competition Sponsor or Kaggle of the required Prize acceptance documents. Transfer or assignment of a Prize is not allowed. \ne. You are not eligible to receive any Prize if you do not meet the Eligibility requirements in Section 2.7 and Section 3.1 above.\nf. If a Team wins a monetary Prize, the Prize money will be allocated in even shares between the eligible Team members, unless the Team unanimously opts for a different Prize split and notifies Kaggle before Prizes are issued.\n\n####10. TAXES\na. ALL TAXES IMPOSED ON PRIZES ARE THE SOLE RESPONSIBILITY OF THE WINNERS. Payments to potential winners are subject to the express requirement that they submit all documentation requested by Competition Sponsor or Kaggle for compliance with applicable state, federal, local and foreign (including provincial) tax reporting and withholding requirements. Prizes will be net of any taxes that Competition Sponsor is required by law to withhold. If a potential winner fails to provide any required documentation or comply with applicable laws, the Prize may be forfeited and Competition Sponsor may select an alternative potential winner. Any winners who are U.S. residents will receive an IRS Form-1099 in the amount of their Prize.\n\n####11. GENERAL CONDITIONS\na. All federal, state, provincial and local laws and regulations apply.\n\n####12. PUBLICITY\na. You agree that Competition Sponsor, Kaggle and its affiliates may use your name and likeness for advertising and promotional purposes without additional compensation, unless prohibited by law.\n\n####13. PRIVACY\na. You acknowledge and agree that Competition Sponsor and Kaggle may collect, store, share and otherwise use personally identifiable information provided by you during the Kaggle account registration process and the Competition, including but not limited to, name, mailing address, phone number, and email address (“Personal Information”). Kaggle acts as an independent controller with regard to its collection, storage, sharing, and other use of this Personal Information, and will use this Personal Information in accordance with its Privacy Policy <[www.kaggle.com/privacy][6]>, including for administering the Competition. As a Kaggle.com account holder, you have the right to request access to, review, rectification, portability or deletion of any personal data held by Kaggle about you by logging into your account and/or contacting Kaggle Support at <[www.kaggle.com/contact][7]>.\nb. As part of Competition Sponsor performing this contract between you and the Competition Sponsor, Kaggle will transfer your Personal Information to Competition Sponsor, which acts as an independent controller with regard to this Personal Information. As a controller of such Personal Information, Competition Sponsor agrees to comply with all U.S. and foreign data protection obligations with regard to your Personal Information. Kaggle will transfer your Personal Information to Competition Sponsor in the country specified in the Competition Sponsor Address listed above, which may be a country outside the country of your residence. Such country may not have privacy laws and regulations similar to those of the country of your residence.\n\n####14. WARRANTY, INDEMNITY AND RELEASE \na. You warrant that your Submission is your own original work and, as such, you are the sole and exclusive owner and rights holder of the Submission, and you have the right to make the Submission and grant all required licenses. You agree not to make any Submission that: (i) infringes any third party proprietary rights, intellectual property rights, industrial property rights, personal or moral rights or any other rights, including without limitation, copyright, trademark, patent, trade secret, privacy, publicity or confidentiality obligations, or defames any person; or (ii) otherwise violates any applicable U.S. or foreign state or federal law.\nb. To the maximum extent permitted by law, you indemnify and agree to keep indemnified Competition Entities at all times from and against any liability, claims, demands, losses, damages, costs and expenses resulting from any of your acts, defaults or omissions and/or a breach of any warranty set forth herein. To the maximum extent permitted by law, you agree to defend, indemnify and hold harmless the Competition Entities from and against any and all claims, actions, suits or proceedings, as well as any and all losses, liabilities, damages, costs and expenses (including reasonable attorneys fees) arising out of or accruing from: (a) your Submission or other material uploaded or otherwise provided by you that infringes any third party proprietary rights, intellectual property rights, industrial property rights, personal or moral rights or any other rights, including without limitation, copyright, trademark, patent, trade secret, privacy, publicity or confidentiality obligations, or defames any person; (b) any misrepresentation made by you in connection with the Competition; (c) any non-compliance by you with these Rules or any applicable U.S. or foreign state or federal law; (d) claims brought by persons or entities other than the parties to these Rules arising from or related to your involvement with the Competition; and (e) your acceptance, possession, misuse or use of any Prize, or your participation in the Competition and any Competition-related activity.\nc. You hereby release Competition Entities from any liability associated with: (a) any malfunction or other problem with the Competition Website; (b) any error in the collection, processing, or retention of any Submission; or (c) any typographical or other error in the printing, offering or announcement of any Prize or winners.\n\n####15. INTERNET\na. Competition Entities are not responsible for any malfunction of the Competition Website or any late, lost, damaged, misdirected, incomplete, illegible, undeliverable, or destroyed Submissions or entry materials due to system errors, failed, incomplete or garbled computer or other telecommunication transmission malfunctions, hardware or software failures of any kind, lost or unavailable network connections, typographical or system/human errors and failures, technical malfunction(s) of any telephone network or lines, cable connections, satellite transmissions, servers or providers, or computer equipment, traffic congestion on the Internet or at the Competition Website, or any combination thereof, which may limit a Participant’s ability to participate.\n\n####16. RIGHT TO CANCEL, MODIFY OR DISQUALIFY\na. If for any reason the Competition is not capable of running as planned, including infection by computer virus, bugs, tampering, unauthorized intervention, fraud, technical failures, or any other causes which corrupt or affect the administration, security, fairness, integrity, or proper conduct of the Competition, Competition Sponsor reserves the right to cancel, terminate, modify or suspend the Competition. Competition Sponsor further reserves the right to disqualify any Participant who tampers with the submission process or any other part of the Competition or Competition Website. Any attempt by a Participant to deliberately damage any website, including the Competition Website, or undermine the legitimate operation of the Competition is a violation of criminal and civil laws. Should such an attempt be made, Competition Sponsor and Kaggle each reserves the right to seek damages from any such Participant to the fullest extent of the applicable law.\n\n####17. NOT AN OFFER OR CONTRACT OF EMPLOYMENT\na. Under no circumstances will the entry of a Submission, the awarding of a Prize, or anything in these Rules be construed as an offer or contract of employment with Competition Sponsor or any of the Competition Entities. You acknowledge that you have submitted your Submission voluntarily and not in confidence or in trust. You acknowledge that no confidential, fiduciary, agency, employment or other similar relationship is created between you and Competition Sponsor or any of the Competition Entities by your acceptance of these Rules or your entry of your Submission.\n\n####18. DEFINITIONS\na. \"Competition Data\" are 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. \nb. An “Entry” is when a Participant has joined, signed up, or accepted the rules of a competition. Entry is required to make a Submission to a competition.\nc. A “Final Submission” is the Submission selected by the user, or automatically selected by Kaggle in the event not selected by the user, that is/are used for final placement on the competition leaderboard.\nd. A “Participant” or “Participant User” is an individual who participates in a competition by entering the competition and making a Submission.\ne. The “Private Leaderboard” is a ranked display of Participants’ Submission scores against the private test set. The Private Leaderboard determines the final standing in the competition.\nf. The “Public Leaderboard” is a ranked display of Participants’ Submission scores against a representative sample of the test data. This leaderboard is visible throughout the competition.\ng. A “Sponsor” is responsible for hosting the competition, which includes but is not limited to providing the data for the competition, determining winners, and enforcing competition rules.\nh. A “Submission” is anything provided by the Participant to the Sponsor to be evaluated for competition purposes and determine leaderboard position. A Submission may be made as a model, notebook, prediction file, or other format as determined by the Sponsor.\ni. A “Team” is one or more Participants participating together in a Kaggle competition, by officially merging together as a Team within the competition platform.\n\n [1]: https://www.treasury.gov/resource-center/sanctions/Programs/Pages/Programs.aspx\n [2]: http://www.kaggle.com/terms\n [3]: http://www.opensource.org\n [4]: http://www.opensource.org\n [5]: https://www.kaggle.com/WinningModelDocumentationGuidelines\n [6]: http://www.kaggle.com/privacy\n [7]: http://www.kaggle.com/contact\n", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false } ] }