{
  "fetched_at": "2026-10-20T05:48:20Z",
  "source_url": "https://www.kaggle.com/competitions/2024-zjutest-1/data",
  "pages": [
    {
      "name": "data-description",
      "content": "train.csv - the training set\n\ntest.csv - the test set\n\nsampleSubmission.csv - a sample submission file in the correct format",
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    {
      "name": "Description",
      "content": "本次作业的资料是从台当局气象局网站下载的真实观测资料，希望大家利用linear regression或其他方法预测PM2.5的数值。\n\n作业使用丰原站的观测记录，分成train set跟test set，train set是丰原站每个月的前15天所有资料。 test set则是从丰原站剩下的资料中取样出来。\n\ntrain.csv：每个月前15天的完整资料。\n\ntest_X.csv：从剩下的5天资料中取样出连续的10小时为一笔，前九小时的所有观测数据当作feature，第十小时的PM2.5当作answer。 一共取出60笔不重复的test data，请根据feature预测这60笔的PM2.5。",
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    {
      "name": "rules",
      "content": " - Don't cheat!\n - Apply yourself!\n - Have fun!",
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    {
      "name": "abstract",
      "content": "",
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      "hasIsPublished": false,
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    },
    {
      "name": "TAST1",
      "content": "使用线性回归完成以上数据集的预测。\n",
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    {
      "name": "Evaluation",
      "content": "  ID,TARGET\n    2,0\n    5,0\n    6,0\n    etc.",
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      "hasIsPublished": false,
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}