{
  "id": 317868,
  "title": "Sampled datasets with user ratios maintained",
  "url": "/competitions/h-and-m-personalized-fashion-recommendations/discussion/317868",
  "author_name": "",
  "post_date": "2022-04-09T09:18:47.073426700Z",
  "votes": 8,
  "comment_count": 1,
  "views": 0,
  "content": "<p>We have three types of users.<br>\n<strong>not_cold_users</strong>: Those who purchased within 3 months and have purchased a total of 5 or more so far.<br>\n<strong>cold_inactive_users</strong>: Those who have purchased less than 5 items and have not purchased in the last 3 months<br>\n<strong>cold_active_users</strong>: Those who have purchased less than 5 and have purchased in the last 3 months</p>\n<p>Because the characteristics of the three types of users are completely different, \bI created the dataset according to the user ratio.</p>\n<p><strong>I hope everyone uses this dataset to verify the performance of the model easily and quickly.</strong></p>\n<p>Notebook Path: <a href=\"https://www.kaggle.com/code/adldotori/all-in-one-sample-dataset\" target=\"_blank\">https://www.kaggle.com/code/adldotori/all-in-one-sample-dataset</a><br>\nSMALL Dataset(5%): <a href=\"https://www.kaggle.com/datasets/adldotori/hm-small5-dataset\" target=\"_blank\">https://www.kaggle.com/datasets/adldotori/hm-small5-dataset</a><br>\nMINI Dataset(1%): <a href=\"https://www.kaggle.com/datasets/adldotori/hm-mini1-dataset\" target=\"_blank\">https://www.kaggle.com/datasets/adldotori/hm-mini1-dataset</a><br>\nTINY Dataset(0.2%): <a href=\"https://www.kaggle.com/datasets/adldotori/hm-tiny02-dataset\" target=\"_blank\">https://www.kaggle.com/datasets/adldotori/hm-tiny02-dataset</a></p>",
  "messages": [
    {
      "id": "1750054",
      "postDate": "04/09/2022 09:18:47",
      "content": "<p>We have three types of users.<br>\n<strong>not_cold_users</strong>: Those who purchased within 3 months and have purchased a total of 5 or more so far.<br>\n<strong>cold_inactive_users</strong>: Those who have purchased less than 5 items and have not purchased in the last 3 months<br>\n<strong>cold_active_users</strong>: Those who have purchased less than 5 and have purchased in the last 3 months</p>\n<p>Because the characteristics of the three types of users are completely different, \bI created the dataset according to the user ratio.</p>\n<p><strong>I hope everyone uses this dataset to verify the performance of the model easily and quickly.</strong></p>\n<p>Notebook Path: <a href=\"https://www.kaggle.com/code/adldotori/all-in-one-sample-dataset\" target=\"_blank\">https://www.kaggle.com/code/adldotori/all-in-one-sample-dataset</a><br>\nSMALL Dataset(5%): <a href=\"https://www.kaggle.com/datasets/adldotori/hm-small5-dataset\" target=\"_blank\">https://www.kaggle.com/datasets/adldotori/hm-small5-dataset</a><br>\nMINI Dataset(1%): <a href=\"https://www.kaggle.com/datasets/adldotori/hm-mini1-dataset\" target=\"_blank\">https://www.kaggle.com/datasets/adldotori/hm-mini1-dataset</a><br>\nTINY Dataset(0.2%): <a href=\"https://www.kaggle.com/datasets/adldotori/hm-tiny02-dataset\" target=\"_blank\">https://www.kaggle.com/datasets/adldotori/hm-tiny02-dataset</a></p>",
      "rawMarkdown": "We have three types of users.\n**not\\_cold\\_users**: Those who purchased within 3 months and have purchased a total of 5 or more so far.\n**cold\\_inactive\\_users**: Those who have purchased less than 5 items and have not purchased in the last 3 months\n**cold\\_active\\_users**: Those who have purchased less than 5 and have purchased in the last 3 months\n\nBecause the characteristics of the three types of users are completely different, \bI created the dataset according to the user ratio.\n\n**I hope everyone uses this dataset to verify the performance of the model easily and quickly.**\n\nNotebook Path: https://www.kaggle.com/code/adldotori/all-in-one-sample-dataset\nSMALL Dataset(5%): https://www.kaggle.com/datasets/adldotori/hm-small5-dataset\nMINI Dataset(1%): https://www.kaggle.com/datasets/adldotori/hm-mini1-dataset\nTINY Dataset(0.2%): https://www.kaggle.com/datasets/adldotori/hm-tiny02-dataset",
      "votes": null
    },
    {
      "id": "1770170",
      "postDate": "04/28/2022 04:04:58",
      "content": "<p>This is very useful, thanks for sharing!</p>",
      "rawMarkdown": "This is very useful, thanks for sharing!",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 1770170,
      "author_name": "",
      "author_url": "",
      "post_date": "04/28/2022 04:04:58",
      "content": "<p>This is very useful, thanks for sharing!</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "1750054": "We have three types of users.\n**not\\_cold\\_users**: Those who purchased within 3 months and have purchased a total of 5 or more so far.\n**cold\\_inactive\\_users**: Those who have purchased less than 5 items and have not purchased in the last 3 months\n**cold\\_active\\_users**: Those who have purchased less than 5 and have purchased in the last 3 months\n\nBecause the characteristics of the three types of users are completely different, \bI created the dataset according to the user ratio.\n\n**I hope everyone uses this dataset to verify the performance of the model easily and quickly.**\n\nNotebook Path: https://www.kaggle.com/code/adldotori/all-in-one-sample-dataset\nSMALL Dataset(5%): https://www.kaggle.com/datasets/adldotori/hm-small5-dataset\nMINI Dataset(1%): https://www.kaggle.com/datasets/adldotori/hm-mini1-dataset\nTINY Dataset(0.2%): https://www.kaggle.com/datasets/adldotori/hm-tiny02-dataset",
    "1770170": "This is very useful, thanks for sharing!"
  },
  "source": "meta"
}