{
  "fetched_at": "2026-10-19T18:55:04Z",
  "source_url": "https://www.kaggle.com/competitions/bgudrugchallenge2023/data",
  "pages": [
    {
      "name": "data-description",
      "content": "Three files are included\n\ntrain.csv - the training set\nvalidation_and_test.csv - the test set, some of which is used for the public leaderboard and some for the private leaderboard \nsample submission.csv - a sample submission file in the correct format",
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    {
      "name": "Description",
      "content": "Predict the toxicity to the liver for every molecule based on various features that were extracted from the SMILES (“Simplified Molecular Input Line Entry System\") of the molecule using DeepChem (https://deepchem.io/) ",
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    {
      "name": "Evaluation",
      "content": "The evaluation metric for this competition is AUC: the Area Under the ROC Curve  ([https://en.wikipedia.org/wiki/Receiver_operating_characteristic](url), [https://scikit-learn.org/stable/modules/model_evaluation.html#roc-metrics](url)). \n\nThe Competition leaderboard has two parts. The public leaderboard provides publicly visible submission scores based on a representative sample of the test data. This leaderboard is visible throughout the competition. The private leaderboard, by contrast, tracks model performance using the remainder of the test data. The private leaderboard thus has final say on whose models are best, and hence, who the winners and losers of the Competition will be. Which subset of data is calculated on the private leaderboard or a submission’s performance on the private leaderboard is not released to users until the competition has been closed.\n## Submission Format **For every molecule in the test dataset**, submission files should contain two columns: `Id` and `Predicted` which contains your label prediction of this row. See file `sample submission.csv` which is a submission with random predictions.",
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    {
      "name": "rules",
      "content": "Please see the doc published on Moodle (Exercise 2)",
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