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| author | Daniel Friesel <daniel.friesel@uos.de> | 2022-03-01 08:40:01 +0100 |
|---|---|---|
| committer | Daniel Friesel <daniel.friesel@uos.de> | 2022-03-01 08:40:01 +0100 |
| commit | 9d42e811a1cd70dc87cc96f4d847fb239ae88d64 (patch) | |
| tree | 818929561edd91ad3b6115ec1d6de8e754446457 /README.md | |
| parent | 8813bc4f07bcb6960845beef1d0908bade927215 (diff) | |
Add SKLEARN DECART support
Diffstat (limited to 'README.md')
| -rw-r--r-- | README.md | 1 |
1 files changed, 1 insertions, 0 deletions
@@ -32,6 +32,7 @@ The following variables may be set to alter the behaviour of dfatool components. | `DFATOOL_DTREE_ENABLED` | 0, **1** | Use decision trees in get\_fitted | | `DFATOOL_DTREE_FUNCTION_LEAVES` | 0, **1** | Use functions (fitted via linear regression) in decision tree leaves when modeling numeric parameters with at least three distinct values. If 0, integer parameters are treated as enums instead. | | `DFATOOL_DTREE_SKLEARN_CART` | **0**, 1 | Use sklearn CART ("Decision Tree Regression") algorithm for decision tree generation. Uses binary nodes and supports splits on scalar variables. Overrides `FUNCTION_LEAVES` (=0) and `NONBINARY_NODES` (=0). | +| `DFATOOL_DTREE_SKLEARN_DECART` | **0**, 1 | Use sklearn CART ("Decision Tree Regression") algorithm for decision tree generation. Ignore scalar parameters, thus emulating the DECART algorithm. | | `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: unlimited. | | `DFATOOL_USE_XGBOOST` | **0**, 1 | Use Extreme Gradient Boosting algorithm for decision forest generation. | |