Parameter Value * memory memory: None * steps "steps: [('featureagglomeration', FeatureAgglomeration(affinity='euclidean', compute_full_tree='auto', connectivity=None, linkage='ward', memory=None, n_clusters=3, pooling_func=)), ('adaboostclassifier', AdaBoostClassifier(algorithm='SAMME.R', base_estimator=None, learning_rate=1.0, n_estimators=50, random_state=None))]" @ featureagglomeration "featureagglomeration: FeatureAgglomeration(affinity='euclidean', compute_full_tree='auto', connectivity=None, linkage='ward', memory=None, n_clusters=3, pooling_func=)" @ adaboostclassifier "adaboostclassifier: AdaBoostClassifier(algorithm='SAMME.R', base_estimator=None, learning_rate=1.0, n_estimators=50, random_state=None)" @ featureagglomeration__affinity featureagglomeration__affinity: 'euclidean' @ featureagglomeration__compute_full_tree featureagglomeration__compute_full_tree: 'auto' @ featureagglomeration__connectivity featureagglomeration__connectivity: None @ featureagglomeration__linkage featureagglomeration__linkage: 'ward' * featureagglomeration__memory featureagglomeration__memory: None @ featureagglomeration__n_clusters featureagglomeration__n_clusters: 3 @ featureagglomeration__pooling_func featureagglomeration__pooling_func: @ adaboostclassifier__algorithm adaboostclassifier__algorithm: 'SAMME.R' @ adaboostclassifier__base_estimator adaboostclassifier__base_estimator: None @ adaboostclassifier__learning_rate adaboostclassifier__learning_rate: 1.0 @ adaboostclassifier__n_estimators adaboostclassifier__n_estimators: 50 @ adaboostclassifier__random_state adaboostclassifier__random_state: None Note: @, searchable params in searchcv too.