{
  "id": 575617,
  "title": "2nd Place Solution",
  "content": "<p>To achieve second place, I used AutoGluon, without applying any feature engineering steps.<br>\nThe following parameters were used:</p>\n<pre><code>model = TabularPredictor(label=,\n                        problem_type=,\n                        eval_metric=\n                        )\n\nmodel.fit(\n    train, \n    time_limit=*,\n    excluded_model_types=[],\n    presets=)\n</code></pre>\n<p>Public LB = 0.0000000517, Private LB = 0.0000000499</p>",
  "comments": [],
  "comment_count": 0,
  "messages": [
    {
      "id": 3189841,
      "postDate": "2025-04-29T20:54:24.460Z",
      "content": "<p>To achieve second place, I used AutoGluon, without applying any feature engineering steps.<br>\nThe following parameters were used:</p>\n<pre><code>model = TabularPredictor(label=,\n                        problem_type=,\n                        eval_metric=\n                        )\n\nmodel.fit(\n    train, \n    time_limit=*,\n    excluded_model_types=[],\n    presets=)\n</code></pre>\n<p>Public LB = 0.0000000517, Private LB = 0.0000000499</p>",
      "rawMarkdown": "To achieve second place, I used AutoGluon, without applying any feature engineering steps.\nThe following parameters were used:\n\n\n```python\nmodel = TabularPredictor(label='ev',\n                        problem_type='regression',\n                        eval_metric='mean_squared_error'\n                        )\n\nmodel.fit(\n    train, \n    time_limit=3600*8,\n    excluded_model_types=['KNN'],\n    presets=\"best_quality\")\n\n```\n\nPublic LB = 0.0000000517, Private LB = 0.0000000499",
      "votes": 7
    }
  ],
  "complete": true,
  "source": "live",
  "fetched_at": "2026-10-20T02:32:39Z",
  "competition_id": 94020,
  "competition_slug": "black-jack-smart-effect-of-removal-ml",
  "team_id": 13728558,
  "solution_url": "/competitions/black-jack-smart-effect-of-removal-ml/writeups/thiago-mantuani-2nd-place-solution"
}