{
  "fetched_at": "2026-10-25T01:22:13Z",
  "source_url": "https://www.kaggle.com/competitions/applai-summer-contest-a/data",
  "pages": [
    {
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    {
      "name": "Description",
      "content": "Recently a new mobile phone company was created. The company needs to decide whether it will sell the mobile phones it will create at low or high prices according to the specifications it will provide for the mobile phones.\nThe company has collected mobile phone sales data of various companies for you to help them predict whether the price of mobile phones is high or low.\n",
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    {
      "name": "Evaluation",
      "content": "The evaluation metric for this competition is categorization accuracy, Accuracy is one metric for evaluating classification models. Informally, accuracy is the fraction of predictions our model got right. Formally, accuracy has the following definition:\nAccuracy = Number of correct predictions / Total number of predictions\nFor binary classification, accuracy can also be calculated in terms of positives and negatives as follows:\nAccuracy = (TP+TN) / (TP+TN+FP+FN)\nWhere TP = True Positives, TN = True Negatives, FP = False Positives, and FN = False Negatives.\n\n**Submission Format**\nSubmission file should contain two columns, id and price-range.\nThe file should contain  a header and have the following format:\n| id | price_range |\n| --- | --- |\n| 1 | 0 |",
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    {
      "name": "rules",
      "content": "This is a page where you can include rules that participants must accept before joining. You may wish to include rules like:\n\n - Don't cheat!\n - Apply yourself!\n - Have fun!",
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