{
  "fetched_at": "2026-10-20T00:03:20Z",
  "source_url": "https://www.kaggle.com/competitions/dataprix21/data",
  "pages": [
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      "name": "data-description",
      "content": "This dataset contains data about subjects suffering from metabolic syndrome.\n\n### Data Description\n- train.csv - The training set\n- test.csv - The test set\n- sampleSubmission.csv - A sample submission file in the correct format\n\n### Data Fields\n- Subject Id - An anonymous unique id assigned to every subject.\n- Subject Age - Age of the subject.\n- Gene A to D - Presence of particular genes in the subject.\n- Per mcL quantity of blood cells- Count of blood cells measured in mcL.\n- Breathing rate - Average breathing rate of the subject.\n- Pulse rate - Average pulse rate of the subject.\n- Diagnostic Testing, Carrier Testing, Enzyme Test, Insulin Test, Thyroid Test - Represents result of certain tests conducted on\n                                                                                            the subject. 0 stands for negative result and 1 stands for positive result.\n- Gender - Gender of the subject.\n- Gastrin Defect - Whether the subject has gastrin defect or not.\n- Neural Anomaly - Whether the subject has some neural anomaly or not.\n- Presence of severe allergies - Whether the subject has some severe allergies or not.\n- Premature Delivery - Whether the subject had a premature delivery or not.\n- Assistance needed in fertility - Whether the subject's father needed some assistance in fertility or not.\n- Previous maternal pregnancy record - If the subject is the first pregnancy of the mother.\n- Maternal Abortion count - Count of abortions that the mother had.\n- Per mcL quantity of white blood cells - Count of white blood cells measured in mcL.\n- CMP test results - CMP is a test related to metabolic ability. This column represents the results obtained in it.\n- A high triglyceride level, Reduced HDL, High BP - Were these symptoms suffered by the subject.\n- Metabolic Syndrome Type - This is the target variable. This represents what type of metabolic syndrome the subject has.",
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    {
      "name": "Description",
      "content": "<p>Metabolic syndromes have been surging due to genetic abnormalities and the fast lifestyle that we have in recent times. Some traditional thinkers started blaming the mothers for the metabolic anomaly in their children. You being a Gen Z, want to prove these people wrong by using the power of machine learning and data analysis. Your college club, being keen on Machine learning, did a lot of research in this field and found out that with the correct amount of data, we can gain an early insight in detecting what kind of metabolic syndrome a person can have.  Your team leader Jignesh being a perfectionist wants the accuracy to be quintessential. He gives you a dataset in which there are various factors that can cause metabolic syndromes. He assigns you a task to build and train a model that can predict what kind of metabolic syndrome a person might have.</p>",
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    {
      "name": "Evaluation",
      "content": "<h4>The evaluation metric for this competition is Mean F1 Score.</h4>\n<hr>\n<p>The evaluation metric for this competition is  Mean F1-Score. The F1 score, commonly used in information retrieval, measures accuracy using the statistics precision p and recall r. Precision is the ratio of true positives (tp) to all predicted positives (tp + fp). Recall is the ratio of true positives to all actual positives (tp + fn). \n</p><p>The F1 metric weights recall and precision equally, and a good retrieval algorithm will maximize both precision and recall simultaneously. Thus, moderately good performance on both will be favored over extremely good performance on one and poor performance on the other.</p>\n<h2>Submission Format</h2>\n<p><strong>For every subject in the dataset</strong>, submission files should contain two columns: Subject Id and Metabolic Syndrome Type\n.</p>\n<p>The file should contain a header and have the following format:</p>\n<pre>Subject Id,Metabolic Syndrome Type\n<br>SID0x62bb,Type A<br></pre>",
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    {
      "name": "rules",
      "content": "Radiance'21 website : https://radiance21.in/\n\n### Rules and regulations\n\n- Contest only for college students\n- One account per participant\n- You must fill the google form provided by organizers before entering this competition.\n- No private sharing outside the team\n- The use of external data is strictly prohibited.\n- The notebook should be made public by 04/09/2021 10:00 AM for the special prize.\n\nCompetition timeline Start Date : 28/08/2021 00:00 AM IST End Date : 03/09/2021 11:59 PM IST\n\nSubmission Limit - You may submit a maximum of 8 submissions per day - You may select up to 3 submissions for final evaluation\n\nTeam limit Max team size allowed is 4.",
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