Column one hot encoder
ColumnOneHotEncoder
¶
Bases: BaseEstimator
, TransformerMixin
Source code in tpot2/builtin_modules/column_one_hot_encoder.py
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__init__(columns='auto', drop=None, handle_unknown='error', sparse_output=False, min_frequency=None, max_categories=None)
¶
Parameters:
Name | Type | Description | Default |
---|---|---|---|
columns |
(str, list)
|
|
'auto'
|
drop |
see sklearn.preprocessing.OneHotEncoder
|
|
None
|
handle_unknown |
see sklearn.preprocessing.OneHotEncoder
|
|
None
|
sparse_output |
see sklearn.preprocessing.OneHotEncoder
|
|
None
|
min_frequency |
see sklearn.preprocessing.OneHotEncoder
|
|
None
|
max_categories |
see sklearn.preprocessing.OneHotEncoder
|
|
None
|
Source code in tpot2/builtin_modules/column_one_hot_encoder.py
fit(X, y=None)
¶
Fit OneHotEncoder to X, then transform X.
Equivalent to self.fit(X).transform(X), but more convenient and more efficient. See fit for the parameters, transform for the return value.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
X |
array-like or sparse matrix, shape=(n_samples, n_features)
|
Dense array or sparse matrix. |
required |
y |
Feature labels |
None
|
Source code in tpot2/builtin_modules/column_one_hot_encoder.py
transform(X)
¶
Transform X using one-hot encoding.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
X |
array-like or sparse matrix, shape=(n_samples, n_features)
|
Dense array or sparse matrix. |
required |
Returns:
Name | Type | Description |
---|---|---|
X_out |
sparse matrix if sparse=True else a 2-d array, dtype=int
|
Transformed input. |