{
  "id": 75406,
  "title": "Some reference",
  "url": "/competitions/vsb-power-line-fault-detection/discussion/75406",
  "author_name": "",
  "post_date": "2018-12-21T08:48:32.946797300Z",
  "votes": 12,
  "comment_count": 6,
  "views": 0,
  "content": "<p>I think this competition is an anomaly detection problem.</p>\n\n<p>We can solve this problem using ML or DL and other statistical approach.</p>\n\n<p>In this ticket, I will recommend you some useful reference.</p>\n\n<p>I hope this will help you!</p>\n\n<p>dataset \n<a href=\"https://www.kaggle.com/mlg-ulb/creditcardfraud\">https://www.kaggle.com/mlg-ulb/creditcardfraud</a></p>\n\n<p>article</p>\n\n<p><a href=\"https://medium.com/@curiousily/credit-card-fraud-detection-using-autoencoders-in-keras-tensorflow-for-hackers-part-vii-20e0c85301bd\">https://medium.com/@curiousily/credit-card-fraud-detection-using-autoencoders-in-keras-tensorflow-for-hackers-part-vii-20e0c85301bd</a></p>\n\n<p>paper\nAnomaly Detection : A Survey (you can get this paper by googling)</p>",
  "messages": [
    {
      "id": "443227",
      "postDate": "12/21/2018 08:48:32",
      "content": "<p>I think this competition is an anomaly detection problem.</p>\n\n<p>We can solve this problem using ML or DL and other statistical approach.</p>\n\n<p>In this ticket, I will recommend you some useful reference.</p>\n\n<p>I hope this will help you!</p>\n\n<p>dataset \n<a href=\"https://www.kaggle.com/mlg-ulb/creditcardfraud\">https://www.kaggle.com/mlg-ulb/creditcardfraud</a></p>\n\n<p>article</p>\n\n<p><a href=\"https://medium.com/@curiousily/credit-card-fraud-detection-using-autoencoders-in-keras-tensorflow-for-hackers-part-vii-20e0c85301bd\">https://medium.com/@curiousily/credit-card-fraud-detection-using-autoencoders-in-keras-tensorflow-for-hackers-part-vii-20e0c85301bd</a></p>\n\n<p>paper\nAnomaly Detection : A Survey (you can get this paper by googling)</p>",
      "rawMarkdown": "I think this competition is an anomaly detection problem.\n\nWe can solve this problem using ML or DL and other statistical approach.\n\nIn this ticket, I will recommend you some useful reference.\n\nI hope this will help you!\n\ndataset \nhttps://www.kaggle.com/mlg-ulb/creditcardfraud\n\narticle\n\nhttps://medium.com/@curiousily/credit-card-fraud-detection-using-autoencoders-in-keras-tensorflow-for-hackers-part-vii-20e0c85301bd\n\npaper\nAnomaly Detection : A Survey (you can get this paper by googling)",
      "votes": null
    },
    {
      "id": "443235",
      "postDate": "12/21/2018 09:22:28",
      "content": "<p>very interesting thanks</p>",
      "rawMarkdown": "very interesting thanks",
      "votes": null
    },
    {
      "id": "443449",
      "postDate": "12/21/2018 17:06:16",
      "content": "<p>Formulate the problem as anomaly detection could be one way to go. Or you can use anomaly score as an additional feature.</p>",
      "rawMarkdown": "Formulate the problem as anomaly detection could be one way to go. Or you can use anomaly score as an additional feature.",
      "votes": null
    },
    {
      "id": "443651",
      "postDate": "12/22/2018 03:19:10",
      "content": "<p>Thanks for kind words! </p>",
      "rawMarkdown": "Thanks for kind words!",
      "votes": null
    },
    {
      "id": "443652",
      "postDate": "12/22/2018 03:19:54",
      "content": "<p>Yes, you're right. I will start with anomaly detection and if I needed, use this approach for feature engineering.</p>",
      "rawMarkdown": "Yes, you're right. I will start with anomaly detection and if I needed, use this approach for feature engineering.",
      "votes": null
    },
    {
      "id": "444162",
      "postDate": "12/23/2018 11:44:30",
      "content": "<p>Thanks for throwing some light into this problem. I think I'll start from there.</p>",
      "rawMarkdown": "Thanks for throwing some light into this problem. I think I'll start from there.",
      "votes": null
    },
    {
      "id": "450272",
      "postDate": "01/04/2019 15:51:24",
      "content": "<p>thanks, it helps a lot.</p>",
      "rawMarkdown": "thanks, it helps a lot.",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 443235,
      "author_name": "richarde",
      "author_url": "",
      "post_date": "12/21/2018 09:22:28",
      "content": "<p>very interesting thanks</p>",
      "votes": null,
      "replies": [
        {
          "id": 443651,
          "author_name": "youhanlee",
          "author_url": "",
          "post_date": "12/22/2018 03:19:10",
          "content": "<p>Thanks for kind words! </p>",
          "votes": null,
          "replies": []
        }
      ]
    },
    {
      "id": 443449,
      "author_name": "randxie",
      "author_url": "",
      "post_date": "12/21/2018 17:06:16",
      "content": "<p>Formulate the problem as anomaly detection could be one way to go. Or you can use anomaly score as an additional feature.</p>",
      "votes": null,
      "replies": [
        {
          "id": 443652,
          "author_name": "youhanlee",
          "author_url": "",
          "post_date": "12/22/2018 03:19:54",
          "content": "<p>Yes, you're right. I will start with anomaly detection and if I needed, use this approach for feature engineering.</p>",
          "votes": null,
          "replies": []
        }
      ]
    },
    {
      "id": 444162,
      "author_name": "atmanpatel294",
      "author_url": "",
      "post_date": "12/23/2018 11:44:30",
      "content": "<p>Thanks for throwing some light into this problem. I think I'll start from there.</p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 450272,
      "author_name": "jenghung",
      "author_url": "",
      "post_date": "01/04/2019 15:51:24",
      "content": "<p>thanks, it helps a lot.</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "443227": "I think this competition is an anomaly detection problem.\n\nWe can solve this problem using ML or DL and other statistical approach.\n\nIn this ticket, I will recommend you some useful reference.\n\nI hope this will help you!\n\ndataset \nhttps://www.kaggle.com/mlg-ulb/creditcardfraud\n\narticle\n\nhttps://medium.com/@curiousily/credit-card-fraud-detection-using-autoencoders-in-keras-tensorflow-for-hackers-part-vii-20e0c85301bd\n\npaper\nAnomaly Detection : A Survey (you can get this paper by googling)",
    "443235": "very interesting thanks",
    "443449": "Formulate the problem as anomaly detection could be one way to go. Or you can use anomaly score as an additional feature.",
    "443651": "Thanks for kind words!",
    "443652": "Yes, you're right. I will start with anomaly detection and if I needed, use this approach for feature engineering.",
    "444162": "Thanks for throwing some light into this problem. I think I'll start from there.",
    "450272": "thanks, it helps a lot."
  },
  "source": "meta"
}