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  "fetched_at": "2026-10-19T18:58:44Z",
  "source_url": "https://www.kaggle.com/competitions/deciphering/data",
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      "name": "data-description",
      "content": "THE GOAL IS TO PREDICT WETHER A MANTIS IS SUCCESSFULL OR NOT WHILE HUNTING\n\n## Files\n\n*   **data.csv** - the training set\n*   **test.csv** - the test set\n\n\n",
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      "content": "---\n\nSubmissions are evaluated on accuracy\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,Hunting Success\n    1,0\n    2,1\n    3,0\n    etc.",
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      "content": "**Competition Rules: Deciphering the Mantis Code**\n\n1. **Eligibility:**\n   - Open to participants worldwide.\n   - Must adhere to Kaggle's terms of service and code of conduct.\n\n2. **Team Formation:**\n   - Participants can compete individually or form teams.\n\n3. **Dataset Usage:**\n   - Use only the provided dataset for model training and evaluation.\n   - Do not use external data sources.\n\n4. **Submission Guidelines:**\n   - Submit predictions in the specified format.\n\n5. **Code Sharing:**\n   - Encourage code sharing and collaboration on Kaggle Kernels.\n   - Respect intellectual property rights and give credit where due.\n\n6. **Fair Play:**\n   - Avoid exploiting loopholes or unethical practices.\n\n8. **Timeline:**\n   - Follow the specified timeline for competition milestones.\n   - Submissions must be made before the deadline.\n\n10. **Community Engagement:**\n    - Encourage positive and constructive interactions on the competition forums.\n    - Uphold the collaborative spirit of Kaggle.\n\n11. **Code of Conduct:**\n    - Abide by Kaggle's code of conduct, promoting a respectful and inclusive community.\n\nBy participating in \"Deciphering the Mantis Code,\" you agree to adhere to these rules and contribute to a vibrant and collaborative competition experience. Best of luck! 🏆",
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      "content": "\n---\n\n**Kaggle Competition: Deciphering the Mantis Code**\n\nWelcome to \"Deciphering the Mantis Code,\" a thrilling Kaggle competition that challenges data enthusiasts, ecologists, and machine learning aficionados to decode the intricate secrets of Chinese mantis behavior, we present a synthetic Mantis Dataset, carefully crafted to simulate real-world scenarios and offer a glimpse into the mysterious world of mantis hunting.\n\n**Challenge Overview:**\nDive into the depths of ecological exploration as you navigate through 300,000 records of synthetic mantis encounters. Your mission is to predict hunting success. Will it be the subtle dance of humidity levels, the strategic timing of an ambush, or the size of the prey that determines victory?\n\n**Dataset Highlights:**\n- 300,000 meticulously curated records, each a chapter in the mantis saga.\n- Target variable: \"Hunting Success\" - a binary indicator of triumph or challenge.\n- Predictor variables encompassing humidity levels, time spent hunting, prey size, and more.\n- Embrace the challenge of outliers, mimicking the unpredictable nature of ecological data.\n\n**Why Participate?**\n- Uncover the nuances of mantis behavior and contribute to ecological understanding.\n- Sharpen your data analysis and machine learning skills in a captivating context.\n- Collaborate with a global community of data enthusiasts and researchers.\n\n**Join us on this data-driven expedition and unlock the secrets of the mantis world. The competition awaits – are you ready to crack the Mantis Code?**\n\n---",
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