StackGenVis: Alignment of Data, Algorithms, and Models for Stacking Ensemble Learning Using Performance Metrics
https://doi.org/10.1109/TVCG.2020.3030352
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8.2 KiB
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batch_size='auto', beta_1=0.9,\n beta_2=0.999, early_stopping=False, epsilon=1e-08,\n hidden_layer_sizes=(100,), learning_rate='constant',\n learning_rate_init=0.001, max_fun=15000, max_iter=100,\n momentum=0.9, n_iter_no_change=10, nesterovs_momentum=True,\n power_t=0.5, random_state=42, shuffle=True, solver='sgd',\n tol=0.00081, validation_fraction=0.1, verbose=False,\n warm_start=False)", "params": "{'alpha': [1e-05, 0.00021, 0.00041000000000000005, 0.0006100000000000001, 0.0008100000000000001], 'tol': [1e-05, 0.00041000000000000005, 0.0008100000000000001], 'max_iter': [100], 'activation': ['relu', 'identity', 'logistic', 'tanh'], 'solver': ['adam', 'sgd']}", "eachAlgor": "'MLP'", "AlgorithmsIDsEnd": "1236", "toggle": "0"}} |