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feat(Events): added EventFilter, EventLabeller (#186)
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from sklearn.preprocessing import MinMaxScaler, Normalizer, StandardScaler
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from .sklearn import SKLearnTransformation
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from typing import Literal
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ScalerTypes = Literal['normalize', 'minmax', 'standardize']
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def get_scaler(type: ScalerTypes) -> SKLearnTransformation:
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if type == 'normalize':
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return SKLearnTransformation(Normalizer())
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elif type == 'minmax':
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return SKLearnTransformation(MinMaxScaler(feature_range= (-1, 1)))
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elif type == 'standardize':
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return SKLearnTransformation(StandardScaler())
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else:
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raise Exception("Scaler type not supported")
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