{
  "fetched_at": "2026-10-19T19:06:01Z",
  "source_url": "https://www.kaggle.com/competitions/1cccfd31e08595c2e2a19d5fd94aeba0/data",
  "pages": [
    {
      "name": "data-description",
      "content": "## File descriptions\n\n- **train.csv** - Training data\n- **test.csv** - Test data\n- **sample_submission.csv** - The correct format for submissions\n\n## Data fields\n\n- **date** - Date of the sale data.\n- **store** - Store ID\n- **item** - Item ID\n- **sales** - Number of items sold at particular store on a particular date.",
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    {
      "name": "Description",
      "content": "## Self-Promotion Dive: Time Series\n\nThis is a typical time series prediction problem.\n\nYou are given 4 years of store-item sales data. Predict 3 months of sales for 50 different items at 10 different stores.\n\nCan you be THE-MODERN NOSTRADAMUS who can foretell the sales of the store?\n\nGive it your best shot!",
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    {
      "name": "Evaluation",
      "content": "This competition uses a [SMAPE](https://en.wikipedia.org/wiki/Symmetric_mean_absolute_percentage_error).\n\n## Submission File\nFor each `id` in the test set, you must predict a probability for the `sales` variable.\nThe files must have a header and should look like the following:\n\n```\nid, sales\n0,10\n1,15\n2,20\netc.\n```",
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    },
    {
      "name": "rules",
      "content": "- Pre-trained models and external data are allowed.\n- Hand-labeling is forbidden.\n- You may submit a maximum of 10 entries per day.\n- Show us what you've got! Have fun!",
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      "hasIsPublished": false,
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  ]
}