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Currently, the scaler parameter in make_mapper_pipeline represents an arbitrary scikit-learn estimator which will be interpreted as serving to scale the data. In practice, however, this could be improved for the following reasons:
The scaling step can always be included as part of filter_func (by feeding a Pipeline for the latter), so this optional argument is little more than a convenience feature, which may cause confusion;
Because scaler can only be a scikit-learn estimator, it cannot be edited interactively in plot_interactive_mapper_graph.
To solve 1 and 2 simultaneously, I propose the following:
Make scaler be one of a few simple string choices ('minmax', 'standard', 'robust', and the like).
Allow the user to toggle between these choices in the interactive widgets produced by plot_interactive_mapper_graph.
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Currently, the
scaler
parameter inmake_mapper_pipeline
represents an arbitraryscikit-learn
estimator which will be interpreted as serving to scale the data. In practice, however, this could be improved for the following reasons:filter_func
(by feeding aPipeline
for the latter), so this optional argument is little more than a convenience feature, which may cause confusion;scaler
can only be ascikit-learn
estimator, it cannot be edited interactively inplot_interactive_mapper_graph
.To solve 1 and 2 simultaneously, I propose the following:
scaler
be one of a few simple string choices ('minmax'
,'standard'
,'robust'
, and the like).plot_interactive_mapper_graph
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