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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StackGenVis/cache_dir/joblib/run/GridSearch/a32924a20c3a8483b7f841d3c9c.../metadata.json

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{"duration": 0.792708158493042, "input_args": {"clf": "RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',\n max_depth=None, max_features='auto', max_leaf_nodes=None,\n min_impurity_decrease=0.0, min_impurity_split=None,\n min_samples_leaf=1, min_samples_split=2,\n min_weight_fraction_leaf=0.0, n_estimators='warn',\n n_jobs=None, oob_score=False, random_state=None,\n verbose=0, warm_start=False)", "params": "{'n_estimators': [10, 50]}", "scoring": "{'accuracy': 'accuracy', 'f1_macro': 'f1_weighted', 'precision': 'precision_weighted', 'recall': 'recall_weighted', 'jaccard': 'jaccard_weighted'}", "FI": "1"}}