{
  "fetched_at": "2026-10-20T10:24:37Z",
  "source_url": "https://www.kaggle.com/competitions/can-i-get-into-relationship/data",
  "pages": [
    {
      "name": "data-description",
      "content": "This dataset contains three files, namely train_data, test_data and sample_submission. \n\n## Files\n\n*   **train.csv** - the training set\n*   **test.csv** - the test set\n*   **sample_submission.csv** - a sample submission file in the correct format\n\n\n## Columns\n\n*   `student_no.` - serial no. of the student surveyed\n*   `age` - age of the student\n*   `grades` - college grade of the student\n* `behaviour` - Behaviour of the student, rated from 1 to 10, in a uniform metric\n* `complexion` - skin complexion of the student\n* `looks` - Looks of the student, rated from 1 to 10, in a uniform metric\n* `Annual_family_income` - Annual family income of the student\n* `weight` - weight category of the student\n* `sports_involvement` -  The sport in which the student is most involved\n* `status` - Relationship status of the student, 1 if in a relationship, 0 otherwise",
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    {
      "name": "Description",
      "content": "\n## What is in the data\nThe test data contains eight columns, namely age, grades, behaviour, complexion, looks, annual family income, weight, sports involvement and (relationship) status. 1 means he or she is in a relationship and 0 means otherwise. You have to come up with your model, and submit the prediction for test dataset, which contains all these columns except status. Your answer can be probabilistic, (e.g. status=0.5)",
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    {
      "name": "Evaluation",
      "content": "We have done the same randomization process for the test data and stored it. We will evaluate upon accuracy to that data.\n\n---\n\nSubmissions are evaluated on [Euclidean distance] between the predicted probability and the observed target.\n\n\n## Submission File\nFor each ID in the test set, you must predict a probability for the TARGET variable. The csv file should contain a header and have the following format:\n\n  ID STATUS\n    2                       0\n    5                      0.5\n    6                       1\n    etc.",
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    },
    {
      "name": "rules",
      "content": "\n\n - Don't cheat!\n - Apply yourself!\n - Have fun!",
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    },
    {
      "name": "abstract",
      "content": "This is the home page of the competition. This competition tries to create a fun exercise on beginner level machine learning and data science.\n\n\n**Goal:**Suppose we have surveyed it over 500 college students in Kolkata, and collected their relationship status, along with some other things, like age, weight, family income, favourite sports, complexion, college grades and rated their looks, behaviour in a uniform metric. Now we want to see if we can predict the relationship status, analyzing these attributes.\nN.B.- This is a fake dataset and just a fun exercise in machine learning",
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  ]
}