THIS IS A TEST INSTANCE. ALL YOUR CHANGES WILL BE LOST!!!!
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Change the parameter lists to named parameters like scikit-learn, rather than the ordered set of parameters currently used in MADlib where you can't do things out of order.
sckikit-learn
Code Block |
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class sklearn.neural_network.MLPClassifier(hidden_layer_sizes=(100, ), activation=’relu’, solver=’adam’, alpha=0.0001, batch_size=’auto’, learning_rate=’constant’, learning_rate_init=0.001, power_t=0.5, max_iter=200, shuffle=True, random_state=None, tol=0.0001, verbose=False, warm_start=False, momentum=0.9, nesterovs_momentum=True, early_stopping=False, validation_fraction=0.1, beta_1=0.9, beta_2=0.999, epsilon=1e-08) |
MADlib
Code Block |
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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 validation
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