[bench] numerai-deep regime: official v5 benchmark deep params as the headline numerai cell#36
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… headline numerai cell 30000 trees, lr 0.001, depth 10, 1024 leaves, colsample 0.1, min_data_in_leaf 10000 (docs.numer.ai deep-lgbm-params). Felix: this is the config most Numerai users care about; the example config stays for completeness. min_data maps to min_child_weight for xgboost (hessian=1 per row under squared error, so it is exactly a row count) and is dropped+flagged for catboost (symmetric trees don't support it). numerai timeout 4h -> 12h for the 30k-tree competitor runs. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01EYUXNtCAXDd3zYT71m8YSJ
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Per Felix: the numerai cell most people care about is the official v5 benchmark "deep" config (docs): 30000 trees, lr 0.001, max_depth 10, num_leaves 1024, colsample_bytree 0.1, min_data_in_leaf 10000. The 2000-tree example config stays for completeness.
Mapping notes:
min_data→min_child_weight(hessian = 1/row under squared error, so it's exactly a row count)min_data_droppedflag (symmetric trees don't support it)🤖 Generated with Claude Code
https://claude.ai/code/session_01EYUXNtCAXDd3zYT71m8YSJ