# encoders#

Encoders for encoding categorical variables and scaling continuous data.

Functions

Classes

 EncoderNormalizer([method, center, ...]) Special Normalizer that is fit on each encoding sequence. Expm1Transform([cache_size]) GroupNormalizer([method, groups, center, ...]) Normalizer that scales by groups. MinusOneTransform([cache_size]) Transform x -> x - 1. MultiNormalizer(normalizers) Normalizer for multiple targets. NaNLabelEncoder([add_nan, warn]) Labelencoder that can optionally always encode nan and unknown classes (in transform) as class 0 ReLuTransform([cache_size]) Transform x -> max(0, x). SoftplusTransform([cache_size]) Transform via the mapping $$\text{Softplus}(x) = \log(1 + \exp(x))$$. TorchNormalizer([method, center, ...]) Basic target transformer that can be fit also on torch tensors. Mixin for providing pre- and post-processing capabilities to encoders.