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docstring do método apply

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matheus_cascalho 2020-12-07 15:56:34 -03:00
parent b9995e780a
commit 81036e506f
1 changed files with 16 additions and 3 deletions
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19
pyFTS/common/transformations/som.py
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@ -26,12 +26,25 @@ class SOMTransformation(Transformation):
def apply(self,
data: pd.DataFrame,
endogen_variable=None,
names: List[str] = ['x', 'y'],
names: Tuple[str] = ('x', 'y'),
param=None,
**kwargs): #TODO(CASCALHO) MELHORAR DOCSTRING
**kwargs):
"""
Transform dataset from M-DIMENSION to 3-dimension
Transform a M-dimensional dataset into a 3-dimensional dataset, where one dimension is the endogen variable
If endogen_variable = None, the last column will be the endogen_variable.
Args:
data (pd.DataFrame): M-Dimensional dataset
endogen_variable (str): column of dataset
names (Tuple): names for new columns created by SOM Transformation.
param:
**kwargs: params of SOM's train process
percentage_train (float). Percentage of dataset that will be used for train SOM network. default: 0.7
leaning_rate (float): leaning rate of SOM network. default: 0.01
epochs: epochs of SOM network. default: 10000
Returns:
"""
if endogen_variable not in data.columns:
endogen_variable = None
cols = data.columns[:-1] if endogen_variable is None else [col for col in data.columns if