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@@ -110,7 +110,8 @@ The following variables may be set to alter the behaviour of dfatool components. | `DFATOOL_DTREE_NONBINARY_NODES` | 0, **1** | Enable non-binary nodes (i.e., nodes with more than two children corresponding to enum variables) in decision trees | | `DFATOOL_DTREE_IGNORE_IRRELEVANT_PARAMS` | 0, **1** | Ignore parameters deemed irrelevant by stddev heuristic during regression tree generation | | `DFATOOL_DTREE_LOSS_IGNORE_SCALAR` | **0**, 1 | Ignore scalar parameters when computing the loss for split node candidates. Instead of computing the loss of a single partition for each `x_i == j`, compute the loss of partitions for `x_i == j` in which non-scalar parameters vary and scalar parameters are constant. This way, scalar parameters do not affect the decision about which non-scalar parameter to use for splitting. | -| `DFATOOL_PARAM_CATEGORIAL_TO_SCALAR` | **0**, 1 | Some models (e.g. sklearn CART, XGBoost) do not support categorial parameters. Ignore them (0) or convert them to scalar indexes (1). | +| `DFATOOL_PARAM_CATEGORIAL_TO_SCALAR` | **0**, 1 | Some models (e.g. FOL, sklearn CART, XGBoost) do not support categorial parameters. Ignore them (0) or convert them to scalar indexes (1). | +| `DFATOOL_FIT_FOL` | **0**, 1 | Build a first-order linear function (i.e., a * param1 + b * param2 + ...) instead of more complex functions or tree structures. | ## Examples |