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It would be nice if we could make feature_info, trim_min, trim_max, and trim_tolerance attributes of the Modeler object. We can still expose these things in the fast_predict function. We could use the values if they are provided and not None. Otherwise, we check for the presence of these attributes and, if specified, use them instead. For feature_info, it must be able to be found as an attribute if None/not specified in the call to fast_predict. For trim_min/trim_max, if it's both None/unspecified and cannot be found as an attribute, the default value None will be used for (no trimming). For trim_tolerance, if it's both None/unspecified and cannot be found as an attribute, the default value of 0.4998 will be used.
This should make it possible to call fast_predict with only the data and a Modeler object.
The text was updated successfully, but these errors were encountered:
It would be nice if we could make
feature_info
,trim_min
,trim_max
, andtrim_tolerance
attributes of theModeler
object. We can still expose these things in thefast_predict
function. We could use the values if they are provided and notNone
. Otherwise, we check for the presence of these attributes and, if specified, use them instead. Forfeature_info
, it must be able to be found as an attribute ifNone
/not specified in the call tofast_predict
. Fortrim_min
/trim_max
, if it's bothNone
/unspecified and cannot be found as an attribute, the default valueNone
will be used for (no trimming). Fortrim_tolerance
, if it's bothNone
/unspecified and cannot be found as an attribute, the default value of0.4998
will be used.This should make it possible to call
fast_predict
with only the data and aModeler
object.The text was updated successfully, but these errors were encountered: