towhee.hub.builtin.operators.feature_engineer.cate_one_hot_encoder

class towhee.hub.builtin.operators.feature_engineer.cate_one_hot_encoder(name: Optional[str] = None)

Bases: StatefulOperator

Standardize numerical features by removing the mean and scaling to unit variance.

Examples:

>>> from towhee import DataCollection, Entity
>>> dc = (
...     DataCollection(['a','b','c','a','b']).map(lambda x: Entity(a=x))
...         .set_training()
...         .cate_one_hot_encoder['a', 'b'](name='one_hot_encoder')
... )

>>> [x.b.nonzero()[1][0] for x in dc.to_list()]
[0, 1, 2, 0, 1]

Methods

feed
fit
predict
set_state
set_training

Attributes

flag
key
metainfo
shared_type

__call__(*args, **kws)

The framework calls __call__ function repeatedly for every input data.

Args:

Returns:

Raises:

An exception during __init__ can terminate the graph run. –

__init__(name: Optional[str] = None)

Init operator, before a graph starts, the framework will call Operator __init__ function.

Args:

Raises:

An exception during __init__ can terminate the graph run. –