> ## Documentation Index
> Fetch the complete documentation index at: https://aidflow.aigensys.com/llms.txt
> Use this file to discover all available pages before exploring further.

# WoeEncoderWorker.fit

**def WoeEncoderWorker.fit**(self, inputs, fx\_choice=REG.GINI, \*\*params) [\[source\]](https://github.com/aigensys-labs/aidflow/blob/main/AID/\TRUENAS\aig_modeling_Products\AID\1_0_Lib\AID\data\encode\woe_encoder.py#L677)

Fit WOE encoding on all encoded features.

For each feature: prunes bins using the selected strategy
(Gini or t-test), computes WOE values, gates on predictive
power, and stores the final encoding.

#### Parameters

**`inputs`** : *`WoeEncoderEnvelope | WoeEncoderInput`*
Input configuration containing train\_set, target, and\
feature lists.

**`fx_choice`** : *`str`*
The bin pruning strategy. Defaults to REG.GINI.

**`**params`** : *`dict`*
Runtime parameters passed to the internal fitter\
(gini\_cutoff, woe\_alpha).

#### Returns

*`WoeEncoder`*
The fitted encoder instance.


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