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| author | Birte Kristina Friesel <birte.friesel@uos.de> | 2024-01-12 09:24:23 +0100 |
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| committer | Birte Kristina Friesel <birte.friesel@uos.de> | 2024-01-12 09:24:23 +0100 |
| commit | c3043d8537e4dceb303929582dab92a6024924ce (patch) | |
| tree | 952cf10ea377e45d56436c7282d6dd925774c720 /README.md | |
| parent | 2cdc0ebc4a68d44dd6381d7fd473455f1d2f1b5d (diff) | |
Expose DFATOOL_ULS_MIN_DISTINCT_VALUES training hyper-parameter
Diffstat (limited to 'README.md')
| -rw-r--r-- | README.md | 1 |
1 files changed, 1 insertions, 0 deletions
@@ -119,6 +119,7 @@ The following variables may be set to alter the behaviour of dfatool components. | `DFATOOL_DTREE_LMT` | **0**, 1 | Use [Linear Model Tree](https://github.com/cerlymarco/linear-tree) algorithm for regression tree generation. Uses binary nodes and linear functions. Overrides `FUNCTION_LEAVES` (=0) and `NONBINARY_NODES` (=0). | | `DFATOOL_CART_MAX_DEPTH` | **0** .. *n* | maximum depth for sklearn CART. Default (0): unlimited. | | `DFATOOL_ULS_ERROR_METRIC` | **rmsd**, mae, p50, p90 | Error metric to use when selecting best-fitting function during unsupervised least squares (ULS) regression. Least squares regression itself minimzes root mean square deviation (rmsd), hence rmsd is the default. | +| `DFATOOL_ULS_MIN_DISTINCT_VALUES` | 2 .. **3** .. *n* | Minimum number of unique values a parameter must take to be eligible for ULS | | `DFATOOL_USE_XGBOOST` | **0**, 1 | Use Extreme Gradient Boosting algorithm for decision forest generation. | | `DFATOOL_XGB_N_ESTIMATORS` | 1 .. **100** .. *n* | Number of estimators (i.e., trees) for XGBoost. Mandatory. | | `DFATOOL_XGB_MAX_DEPTH` | 2 .. **10** .. *n* | Maximum XGBoost tree depth. XGBoost default: 6 | |