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| author | Birte Kristina Friesel <birte.friesel@uos.de> | 2024-01-18 15:53:07 +0100 |
|---|---|---|
| committer | Birte Kristina Friesel <birte.friesel@uos.de> | 2024-01-18 15:53:07 +0100 |
| commit | f4cd1ae0e118b1975b8400ca4047a1d5ca7e20c1 (patch) | |
| tree | 17688b2512b93fbcacf7c1f413c6a997b68caecd | |
| parent | 2886cb1f2579742d84c017d647a9add045e5481e (diff) | |
Rename DFATOOL_{'' → ULS_}SKIP_CODEPENDENT_CHECK
| -rw-r--r-- | README.md | 2 | ||||
| -rw-r--r-- | doc/modeling-method.md | 2 | ||||
| -rw-r--r-- | lib/parameters.py | 2 |
3 files changed, 3 insertions, 3 deletions
@@ -120,7 +120,7 @@ The following variables may be set to alter the behaviour of dfatool components. | `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_SKIP_CODEPENDENT_CHECK` | **0**, 1 | Do not detect and remove co-dependent features in ULS. | +| `DFATOOL_ULS_SKIP_CODEPENDENT_CHECK` | **0**, 1 | Do not detect and remove co-dependent features in 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 | diff --git a/doc/modeling-method.md b/doc/modeling-method.md index f369cc0..dab120e 100644 --- a/doc/modeling-method.md +++ b/doc/modeling-method.md @@ -41,7 +41,7 @@ All of these are valid regression model trees. * `DFATOOL_FIT_LINEAR_ONLY=1` makes RMT behave more like LMT by only considering linear functions in leaf nodes. * `DFATOOL_FIT_FOL=1` * `DFATOOL_PARAM_CATEGORIAL_TO_SCALAR=1` -* `DFATOOL_SKIP_CODEPENDENT_CHECK=1` +* `DFATOOL_ULS_SKIP_CODEPENDENT_CHECK=1` * `DFATOOL_REGRESSION_SAFE_FUNCTIONS=1` ## diff --git a/lib/parameters.py b/lib/parameters.py index b5bd53a..00ab70a 100644 --- a/lib/parameters.py +++ b/lib/parameters.py @@ -282,7 +282,7 @@ def codependent_param_dict(param_values): if not len(param_values): logger.warning("codependent_param_dict called with param_values=[]") return dict() - if bool(int(os.getenv("DFATOOL_SKIP_CODEPENDENT_CHECK", 0))): + if bool(int(os.getenv("DFATOOL_ULS_SKIP_CODEPENDENT_CHECK", 0))): return dict() lut = [dict() for i in param_values[0]] for param_index in range(len(param_values[0])): |