{
  "fetched_at": "2026-10-19T08:11:16Z",
  "source_url": "https://www.kaggle.com/competitions/aiskbs/data",
  "pages": [
    {
      "name": "data-description",
      "content": "<!--## Files\n\n*   **train.csv** - the training set. Use this to train and validate your model.\n*   **test.csv** - the test set. Use this for making your submission.\n*   **sample_submission.csv** - a sample submission file in the correct format\n\nThe `train.csv` and `test.csv` files contain 768 feature columns (f_0 through f_767). In addition to these feature columns, the train.csv file contains an additional `label` column which denotes the category of each sample (feature-set).\n-->",
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      "postTitle": "",
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    },
    {
      "name": "Description",
      "content": "<!--In this competition, you are tasked to classify a given set of features into five distinct classes.\n\nThe dataset consists of 768 features extracted from textual data and the five classes represent the sentiment expressed by the original text. The classes are:\n1. Extremely Negative\n2. Negative\n3. Neutral\n4. Positive\n5. Extremely Positive\n\nAll the Best!\n\nP.S.: you can make a maximum of 10 submissions in a day.-->",
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      "hasIsPublished": false,
      "postTitle": "",
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    },
    {
      "name": "Evaluation",
      "content": "<!--\n\nThe evaluation metric for this competition is [Mean F1-Score](https://en.wikipedia.org/wiki/F-score). The F1 score, commonly used in information retrieval, measures accuracy using the statistics precision and recall.\nThe F1 metric weights recall and precision equally, and a good retrieval algorithm will maximize both precision and recall simultaneously. Thus, moderately good performance on both will be favored over extremely good performance on one and poor performance on the other.\n\n## Submission Format\n\n**For every sample in the test data**, submission files should contain two columns: `Id` and `Predicted`. \n\nThe file should contain a header and have the following format:\n```\nId,Predicted\n0,4\n1,0\n2,2\n``` -->",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
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      "mimeType": "",
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    },
    {
      "name": "rules",
      "content": "The rules are pretty simle:\n\n\n- Don't cheat!\n- Have fun!",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
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  ]
}