README: Specify that DFATOOL_PARAM_CATEGORIAL_TO_SCALAR=1 sorts lexically

1 files changed, 1 insertions, 1 deletions

diff --git a/README.md b/README.md
index 20071fc..a95718e 100644
--- a/README.md
+++ b/README.md
@@ -138,7 +138,7 @@ The following variables may be set to alter the behaviour of dfatool components.
 | `DFATOOL_DTREE_IGNORE_IRRELEVANT_PARAMS` | **0**, 1 | Ignore parameters deemed irrelevant by stddev heuristic during regression tree generation. Use with caution. |
 | `DFATOOL_PARAM_RELEVANCE_THRESHOLD` | 0 .. **0.5** .. 1 | Threshold for relevant parameter detection: parameter *i* is relevant if mean standard deviation (data partitioned by all parameters) / mean standard deviation (data partition by all parameters but *i*) is less than threshold |
 | `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. FOL, 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). Conversion uses lexical order. |
 | `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. Must not be combined with `--force-tree`. |
 | `DFATOOL_FOL_SECOND_ORDER` || **0**, 1 | Add second-order components (interaction of feature pairs) to first-order linear function. |