From 937bcec1ed1bd379c226aea5eb8ce5ec95264703 Mon Sep 17 00:00:00 2001 From: Daniel Friesel Date: Thu, 27 Jan 2022 10:20:17 +0100 Subject: add LMT support via https://github.com/cerlymarco/linear-tree --- README.md | 1 + 1 file changed, 1 insertion(+) (limited to 'README.md') diff --git a/README.md b/README.md index 50c29e3..4d7354e 100644 --- a/README.md +++ b/README.md @@ -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_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. | | `DFATOOL_XGB_N_ESTIMATORS` | 1 .. **100** .. *n* | Number of estimators (i.e., trees) for XGBoost. | -- cgit v1.2.3