Admission to an Elite High School - OJIA 3 Simulation (v1)

🎓 Elite High School Admission

An extremely important step in every student's personal development is admission to a prestigious, elite high school.
Develop a model that predicts whether, based on multiple results, the candidate will be admitted to an elite high school (status_admitere = 1) or rejected (status_admitere = 0).
You will train the model using the training dataset train_data.csv and then generate predictions using the test dataset test_data.csv.

🗂️ Dataset Description

Training Dataset (train.csv) contains the following columns:

• id (natural number): unique candidate identifier
• gen (M/F): candidate's gender
• judet (2-character string): candidate's county
• NT (1.00-10.00): admission test score
• MEV (6.00-10.00): national evaluation average
• MATE (5.00-10.00): middle school mathematics average
• MGIM (5.00-10.00): general middle school average
• status_admitere (0 or 1): 1 = admitted, 0 = rejected

Prediction Dataset (test.csv):

• 180 samples with the same characteristics (id, gen, judet, NT, MEV, MATE, MGIM) as the training set, without the status_admitere column.
• Your model will generate predictions for these samples.

📊 Expected Output

The submission file output.csv must contain exactly three columns: subtaskID, datapointID, answer.

Important: Each row in the CSV represents the answer for a single subtask and a single datapoint. For each datapointID there must be one row for each subtask.

🏆 Score

Submitting the sample_output.csv file generates 5 points.

⚙️ Notes

• Remove irrelevant columns for prediction.
• Standardize numerical columns.
• There are no incomplete rows.
• Consult the Starter Kit section for guidance details about data format and submission.

🗂️ Useful Resources

• Complete Starter Kit – contains a skeleton from which you can start solving the problem