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    "name": "Solar-Radiation-Prediction",
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    "description": "Context\nSpace Apps Moscow was held on April 29th  30th. Thank you to the 175 people who joined the International Space Apps Challenge at this location!\nContent\nThe dataset contains such columns as: \"wind direction\", \"wind speed\", \"humidity\" and temperature. The response parameter that is to be predicted is: \"Solar_radiation\". It contains measurements for the past 4 months and you have to predict the level of solar radiation.\nJust imagine that you've got solar energy batteries and you want to know will it  be reasonable to use them in future?\nAcknowledgements\nThanks NASA for the dataset.\nInspiration\nPredict the level of solar radiation.\nHere are some intersecting dependences that i have figured out:\n\nHumidity  Solarradiation.\n2.Temeperature  Solarradiation.\n\nThe best result of accuracy  I could get using cross-validation was only 55.",
    "format": "arff",
    "uploader": "Dustin Carrion",
    "uploader_id": 30123,
    "visibility": "public",
    "creator": null,
    "contributor": null,
    "date": "2022-03-24 07:51:26",
    "update_comment": null,
    "last_update": "2022-03-24 07:51:26",
    "licence": "Database: Open Database, Contents: Database Contents",
    "status": "active",
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