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Added support for 1D-List Features in OneHotEncodingTransformer

@JoeriHermans
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Hi,

Thanks for your contribution! Before merging, could you provide a usage example of this particular feature? Since it might impact performance to some extend.

Joeri

@raviolli
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raviolli commented Oct 26, 2017

UseCase:

#PERFORM ONE-HOT-ENCODING ON FEATURES
transformer = OneHotTransformer(output_dim=nb_classes, input_col="features", output_col="features_1hot")
dataset_ = transformer.transform(dataset)

Where "features" is an list (1D array) of features. It outputs a 2D np.array of OHE features.

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2 participants