THIS IS A TEST INSTANCE. ALL YOUR CHANGES WILL BE LOST!!!!
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mlp_classification( source_table, output_table, independent_varname, dependent_varname, hidden_layer_sizes, optimizer_params, activation, weights, warm_start, verbose, grouping_col ) |
Interfaces for Cross
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Validation
The general CV interface is clunky and difficult to use. Instead we should aim to incorporate CV capabilities within each relevant function. For example, the Elastic Net CV in scikit-learn includes a ‘cv’ parameter that picks best estimator using cross-validation.
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