{
  "fetched_at": "2026-10-20T08:42:29Z",
  "source_url": "https://www.kaggle.com/competitions/2022-neural-network/data",
  "pages": [
    {
      "name": "data-description",
      "content": "Analysis the data, and predict the quality of the wine.\n\nInput variables (based on physicochemical tests):\n1 - fixed acidity\n2 - volatile acidity\n3 - citric acid\n4 - residual sugar\n5 - chlorides\n6 - free sulfur dioxide\n7 - total sulfur dioxide\n8 - density\n9 - pH\n10 - sulphates\n11 - alcohol\nOutput variable (based on sensory data):\n12 - quality (score between 0 and 10)\n\nTo simply the problem, we transfer quality to two class: bad and good.\nIf quality <= 5: bad (0)\nIf quality > 5: good (1)\n\nAcknowledgements: [https://archive.ics.uci.edu/ml/datasets/wine+quality](https://archive.ics.uci.edu/ml/datasets/wine+quality)",
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    {
      "name": "Description",
      "content": "Analysis the data, and predict the quality of the wine.\n\nInput variables (based on physicochemical tests):\n1 - fixed acidity\n2 - volatile acidity\n3 - citric acid\n4 - residual sugar\n5 - chlorides\n6 - free sulfur dioxide\n7 - total sulfur dioxide\n8 - density\n9 - pH\n10 - sulphates\n11 - alcohol\nOutput variable (based on sensory data):\n12 - quality (score between 0 and 10)\n\nTo simply the problem, we transfer quality to two class: bad and good.\nIf quality <= 5: bad (0)\nIf quality > 5: good (1)\n\nAcknowledgements: [https://archive.ics.uci.edu/ml/datasets/wine+quality](https://archive.ics.uci.edu/ml/datasets/wine+quality)",
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    {
      "name": "Evaluation",
      "content": "- 不限定模型\n- 會以準確率作為評分的標準\n- 每天最多可繳交10次\n- 請不要將你的程式碼公開至kaggle\n- 請將Team name設為你的學號\n- 繳交日期: 10/11 23:59",
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    },
    {
      "name": "rules",
      "content": "- 不限定模型\n- 會以準確率作為評分的標準\n- 每天最多可繳交10次\n- 請不要將你的程式碼公開至kaggle\n- 請將Team name設為你的學號\n- 繳交日期: 10/11 23:59",
      "isPublished": false,
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}