{
  "id": 419933,
  "title": "Competition Split Announcement! 🚀",
  "url": "/competitions/ext-market/discussion/419933",
  "author_name": "",
  "post_date": "2023-06-28T10:56:35.383000",
  "votes": 1,
  "comment_count": 0,
  "views": 0,
  "content": "<p>After carefully considering the unique characteristics of the dataset and your valuable feedback, I have decided to <strong>split the competition into two distinct tracks</strong>. This division aims to provide you with specialized challenges that target specific aspects of the problem at hand. Let's delve into the details of each track:</p>\n<h1>Track 1: Anomaly Detection Challenge (Hold and Combined Minors)</h1>\n<p>In this track, we will focus on <strong>detecting anomalies within the dataset</strong>. The primary goal is to identify instances belonging to the \"hold\" class and the combined set of two smaller minority classes. This track requires participants to develop innovative models and techniques that can accurately distinguish these anomalies from the majority class. By participating in this track, you will contribute to the critical task of anomaly detection, which has wide-ranging applications in various domains.</p>\n<p>url: <a href=\"https://www.kaggle.com/competitions/anomaly-class-detection\" target=\"_blank\">https://www.kaggle.com/competitions/anomaly-class-detection</a></p>\n<h1>Track 2: Buy or Short Classification Challenge (Between Two Minorities)</h1>\n<p>For participants who are passionate about the classification aspect of the problem, we present Track 2. Here, the challenge is to predict whether a given instance belongs to the \"buy\" class or the \"short\" class, both of which are part of the two smaller minority classes. By focusing exclusively on these two classes, you will have the opportunity to explore the nuances of differentiating between them and build models that can make accurate predictions in this specific scenario.</p>\n<p>url: <a href=\"https://www.kaggle.com/competitions/shortlong-prediction\" target=\"_blank\">https://www.kaggle.com/competitions/shortlong-prediction</a></p>\n<p><strong>Good luck to all participants, and let the anomaly detection and buy/short classification challenges begin!</strong></p>",
  "messages": [
    {
      "id": 2321177,
      "postDate": "2023-06-28T10:56:35.383Z",
      "content": "<p>After carefully considering the unique characteristics of the dataset and your valuable feedback, I have decided to <strong>split the competition into two distinct tracks</strong>. This division aims to provide you with specialized challenges that target specific aspects of the problem at hand. Let's delve into the details of each track:</p>\n<h1>Track 1: Anomaly Detection Challenge (Hold and Combined Minors)</h1>\n<p>In this track, we will focus on <strong>detecting anomalies within the dataset</strong>. The primary goal is to identify instances belonging to the \"hold\" class and the combined set of two smaller minority classes. This track requires participants to develop innovative models and techniques that can accurately distinguish these anomalies from the majority class. By participating in this track, you will contribute to the critical task of anomaly detection, which has wide-ranging applications in various domains.</p>\n<p>url: <a href=\"https://www.kaggle.com/competitions/anomaly-class-detection\" target=\"_blank\">https://www.kaggle.com/competitions/anomaly-class-detection</a></p>\n<h1>Track 2: Buy or Short Classification Challenge (Between Two Minorities)</h1>\n<p>For participants who are passionate about the classification aspect of the problem, we present Track 2. Here, the challenge is to predict whether a given instance belongs to the \"buy\" class or the \"short\" class, both of which are part of the two smaller minority classes. By focusing exclusively on these two classes, you will have the opportunity to explore the nuances of differentiating between them and build models that can make accurate predictions in this specific scenario.</p>\n<p>url: <a href=\"https://www.kaggle.com/competitions/shortlong-prediction\" target=\"_blank\">https://www.kaggle.com/competitions/shortlong-prediction</a></p>\n<p><strong>Good luck to all participants, and let the anomaly detection and buy/short classification challenges begin!</strong></p>",
      "rawMarkdown": "After carefully considering the unique characteristics of the dataset and your valuable feedback, I have decided to **split the competition into two distinct tracks**. This division aims to provide you with specialized challenges that target specific aspects of the problem at hand. Let's delve into the details of each track:\n\n# Track 1: Anomaly Detection Challenge (Hold and Combined Minors)\n\nIn this track, we will focus on **detecting anomalies within the dataset**. The primary goal is to identify instances belonging to the \"hold\" class and the combined set of two smaller minority classes. This track requires participants to develop innovative models and techniques that can accurately distinguish these anomalies from the majority class. By participating in this track, you will contribute to the critical task of anomaly detection, which has wide-ranging applications in various domains.\n\nurl: https://www.kaggle.com/competitions/anomaly-class-detection\n\n# Track 2: Buy or Short Classification Challenge (Between Two Minorities)\nFor participants who are passionate about the classification aspect of the problem, we present Track 2. Here, the challenge is to predict whether a given instance belongs to the \"buy\" class or the \"short\" class, both of which are part of the two smaller minority classes. By focusing exclusively on these two classes, you will have the opportunity to explore the nuances of differentiating between them and build models that can make accurate predictions in this specific scenario.\n\nurl: https://www.kaggle.com/competitions/shortlong-prediction\n\n**Good luck to all participants, and let the anomaly detection and buy/short classification challenges begin!**\n",
      "votes": 1
    }
  ],
  "comments": [],
  "raw_markdown_by_id": {
    "2321177": "After carefully considering the unique characteristics of the dataset and your valuable feedback, I have decided to **split the competition into two distinct tracks**. This division aims to provide you with specialized challenges that target specific aspects of the problem at hand. Let's delve into the details of each track:\n\n# Track 1: Anomaly Detection Challenge (Hold and Combined Minors)\n\nIn this track, we will focus on **detecting anomalies within the dataset**. The primary goal is to identify instances belonging to the \"hold\" class and the combined set of two smaller minority classes. This track requires participants to develop innovative models and techniques that can accurately distinguish these anomalies from the majority class. By participating in this track, you will contribute to the critical task of anomaly detection, which has wide-ranging applications in various domains.\n\nurl: https://www.kaggle.com/competitions/anomaly-class-detection\n\n# Track 2: Buy or Short Classification Challenge (Between Two Minorities)\nFor participants who are passionate about the classification aspect of the problem, we present Track 2. Here, the challenge is to predict whether a given instance belongs to the \"buy\" class or the \"short\" class, both of which are part of the two smaller minority classes. By focusing exclusively on these two classes, you will have the opportunity to explore the nuances of differentiating between them and build models that can make accurate predictions in this specific scenario.\n\nurl: https://www.kaggle.com/competitions/shortlong-prediction\n\n**Good luck to all participants, and let the anomaly detection and buy/short classification challenges begin!**\n"
  }
}