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Description
[(0.666667, SimpleRegressionPipeline({'imputation:strategy': 'mean', 'one_hot_encoding:use_minimum_fraction': 'True', 'preprocessor:choice': 'no_preprocessing', 'regressor:choice': 'adaboost', 'rescaling:choice': 'minmax', 'one_hot_encoding:minimum_fraction': 0.010000000000000004, 'regressor:adaboost:learning_rate': 0.9890631979261445, 'regressor:adaboost:loss': 'linear', 'regressor:adaboost:max_depth': 10, 'regressor:adaboost:n_estimators': 127}, dataset_properties={ 'task': 4, 'sparse': False, 'multilabel': False, 'multiclass': False, 'target_type': 'regression', 'signed': False})), (0.333333, SimpleRegressionPipeline({'imputation:strategy': 'mean', 'one_hot_encoding:use_minimum_fraction': 'True', 'preprocessor:choice': 'random_trees_embedding', 'regressor:choice': 'liblinear_svr', 'rescaling:choice': 'standardize', 'one_hot_encoding:minimum_fraction': 0.00011808426850838513, 'preprocessor:random_trees_embedding:max_depth': 3, 'preprocessor:random_trees_embedding:max_leaf_nodes': 'None', 'preprocessor:random_trees_embedding:min_samples_leaf': 3, 'preprocessor:random_trees_embedding:min_samples_split': 3, 'preprocessor:random_trees_embedding:min_weight_fraction_leaf': 1.0, 'preprocessor:random_trees_embedding:n_estimators': 68, 'regressor:liblinear_svr:C': 1.4174149191248073, 'regressor:liblinear_svr:dual': 'False', 'regressor:liblinear_svr:epsilon': 0.0328370684051209, 'regressor:liblinear_svr:fit_intercept': 'True', 'regressor:liblinear_svr:intercept_scaling': 1, 'regressor:liblinear_svr:loss': 'squared_epsilon_insensitive', 'regressor:liblinear_svr:tol': 0.0012221149693867595}, dataset_properties={ 'task': 4, 'sparse': False, 'multilabel': False, 'multiclass': False, 'target_type': 'regression', 'signed': False})), ] R2 score: 0.87227602958 How to convert the model I run to sklearn code？could you give me some example code?