PreviousImputer¶
Imputes missing values by using the most recent value.
Examples¶
from river import preprocessing
imputer = preprocessing.PreviousImputer()
imputer.learn_one({'x': 1, 'y': 2})
imputer.transform_one({'y': None})
{'y': 2}
imputer.transform_one({'x': None})
{'x': 1}
Methods¶
learn_one
Update with a set of features x
.
A lot of transformers don't actually have to do anything during the learn_one
step because they are stateless. For this reason the default behavior of this function is to do nothing. Transformers that however do something during the learn_one
can override this method.
Parameters
- x — 'dict'
transform_one
Transform a set of features x
.
Parameters
- x — 'dict'
Returns
dict: The transformed values.