HF RL Explorer

Task 236

Task 236: train task in FineEnvs/smoldataenv-multi-harness-whitebox, an RL environment on the Hugging Face Hub. You are a data-analysis agent working in a sandbox. Use your code-execution tool to inspect the files and compute the answer. Files (in /home/user/input, no subfolders): - Video Games…

The task

You are a data-analysis agent working in a sandbox. Use your code-execution tool to inspect the files and compute the answer. Files (in /home/user/input, no subfolders): - Video_Games_Sales_as_at_22_Dec_2016.csv Installed: pandas, numpy, matplotlib, seaborn, scipy, scikit-learn, statsmodels, tabulate, sqlite3, plotly (pip install more if needed). Question: Among the three models (Lasso, Ridge, Random Forest), which achieved the highest test R² score for predicting European sales (eu_sales)? Work it out step by step — inspect the data first (head, shape, dtypes), then compute. Answer with a single clean value: a bare number (no commas or units, e.g. 95293), a short label, yes/no, or a comma-separated list. Keep decimal precision. If there's no applicable answer, write: Not Applicable Write only that value to /workdir/answer.txt (e.g. `echo -n "<value>" > /workdir/answer.txt`), then stop.

Task details

difficulty
hard