from sklearn.preprocessing.label import LabelEncoder as SKLModel
import lale.helpers
import lale.operators
from numpy import nan, inf
[docs]class LabelEncoderImpl():
def __init__(self):
self._hyperparams = {
}
[docs] def fit(self, X, y=None):
self._sklearn_model = SKLModel(**self._hyperparams)
if (y is not None):
self._sklearn_model.fit(X, y)
else:
self._sklearn_model.fit(X)
return self
_hyperparams_schema = {
'$schema': 'http://json-schema.org/draft-04/schema#',
'description': 'inherited docstring for LabelEncoder Encode labels with value between 0 and n_classes-1.',
'allOf': [{
'type': 'object',
'properties': {
}}],
}
_input_fit_schema = {
'$schema': 'http://json-schema.org/draft-04/schema#',
'description': 'Fit label encoder',
'type': 'object',
'properties': {
'y': {
'type': 'array',
'items': {
'type': 'number'},
'description': 'Target values.'},
},
}
_input_transform_schema = {
'$schema': 'http://json-schema.org/draft-04/schema#',
'description': 'Transform labels to normalized encoding.',
'type': 'object',
'properties': {
'y': {
'type': 'array',
'items': {
'type': 'number'},
'description': 'Target values.'},
},
}
_output_transform_schema = {
'$schema': 'http://json-schema.org/draft-04/schema#',
'description': 'Transform labels to normalized encoding.',
'type': 'array',
'items': {
'type': 'number'},
}
_combined_schemas = {
'$schema': 'http://json-schema.org/draft-04/schema#',
'description': 'Combined schema for expected data and hyperparameters.',
'type': 'object',
'tags': {
'pre': [],
'op': ['transformer'],
'post': []},
'properties': {
'hyperparams': _hyperparams_schema,
'input_fit': _input_fit_schema,
'input_transform': _input_transform_schema,
'output_transform': _output_transform_schema},
}
if (__name__ == '__main__'):
lale.helpers.validate_is_schema(_combined_schemas)
LabelEncoder = lale.operators.make_operator(LabelEncoderImpl, _combined_schemas)