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add syntactic cases for xgboost #200

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Nov 24, 2025
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add syntactic cases for xgboost #200

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50 changes: 50 additions & 0 deletions configs/weekly/xgboost_regression.json
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Original file line number Diff line number Diff line change
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{
"INCLUDE": ["../common/xgboost.json"],
"PARAMETERS_SETS": {
"xgboost data": [
{
"data": {
"source": "make_regression",
"generation_kwargs": [
{
"n_samples": 2097152, "n_features": 256
},
{
"n_samples": 2097152, "n_features": 32
}
],
"split_kwargs": { "train_size": 0.5, "test_size": 0.5 }
},
"algorithm": {
"estimator_params": [
{
"n_estimators": 128,
"max_depth": 8
Comment on lines +21 to +22
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@david-cortes-intel david-cortes-intel Nov 20, 2025

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Do these parameters make sense without reducing the learning rate? I guess in this case it'd be a toy problem with very high predicatibility, but would the tree structure end up being similar as what you'd get for the original epsilon data?

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@razdoburdin razdoburdin Nov 20, 2025

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sorry for misunderstanding.

this is not the replacement for epsion. This is the toy case I have used for EMR vs GNR performance comparison. We need to have this case in some public benchmarks to be able to share it.

},
{
"n_estimators": 128,
"max_depth": 3
},
{
"n_estimators": 32,
"max_depth": 8
},
{
"n_estimators": 32,
"max_depth": 3
}
]
}
}
]
},
"TEMPLATES": {
"regression": {
"SETS": [
"xgboost regression",
"xgboost implementations",
"xgboost data"
]
}
}
}
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