tensortrade.features.scalers.min_max_normalizer module¶
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class
tensortrade.features.scalers.min_max_normalizer.
MinMaxNormalizer
(columns=None, feature_min=0, feature_max=1, inplace=True)[source]¶ Bases:
tensortrade.features.feature_transformer.FeatureTransformer
A transformer for normalizing values within a feature pipeline by the column-wise extrema.
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__init__
(columns=None, feature_min=0, feature_max=1, inplace=True)[source]¶ - Parameters
columns (optional) – A list of column names to normalize.
feature_min (optional) – The minimum float in the range to scale to. Defaults to 0.
feature_max (optional) – The maximum float in the range to scale to. Defaults to 1.
inplace (optional) – If False, a new column will be added to the output for each input column.
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transform
(X, input_space)[source]¶ Transform the data set and return a new data frame.
- Parameters
X (
DataFrame
) – The set of data to transform.input_space (
Space
) – A gym.Space matching the shape of the pipeline’s input.
- Return type
DataFrame
- Returns
A transformed data frame.
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