AI开发平台ModelArts-梯度提升树回归特征重要性:样例

时间：2023-11-01 16:20:20

AI开发平台ModelArts

样例

inputs = {    "dataframe": None,  # @input {"label":"dataframe","type":"DataFrame"}    "pipeline_model": None,  # @input {"label":"pipeline_model","type":"PipelineModel"}    "gbt_regressor_model": None}params = {    "inputs": inputs,    "input_columns_str": "",  # @param {"label": "input_columns_str", "type": "string", "required": "false", "helpTip": ""}     "label_col": "",  # @param {"label": "label_col", "type": "string", "required": "true", "helpTip": ""}    "model_input_features_col": "model_features",  # @param {"label": "model_input_features_col", "type": "string", "required": "false", "helpTip": ""}     "prediction_col": "prediction",  # @param {"label": "prediction_col", "type": "string", "required": "false", "helpTip": ""}     "max_depth": 5,  # @param {"label": "max_depth", "type": "integer", "required": "false","range":"(0,2147483647]", "helpTip": ""}     "max_bins": 32,  # @param {"label": "max_bins", "type": "integer", "required": "false","range":"(0,2147483647]", "helpTip": ""}     "min_instances_per_node": 1,  # @param {"label": "min_instances_per_node", "type": "integer", "required": "false","range":"(0,2147483647]", "helpTip": ""}     "min_info_gain": 0.0,  # @param {"label": "min_info_gain", "type": "number", "required": "false", "helpTip": ""}    "subsampling_rate": 1.0,  # @param {"label": "subsampling_rate", "type": "number", "required": "false", "helpTip": ""}     "loss_type": "squared",  # @param {"label": "loss_type", "type": "enum", "required": "false", "options": "squared, absolute", "helpTip": ""}     "max_iter": 20,  # @param {"label": "max_iter", "type": "integer", "required": "false","range":"(0,2147483647]", "helpTip": ""}     "step_size": 0.1,  # @param {"label": "step_size", "type": "number", "required": "false", "helpTip": ""}    "impurity": "variance"}gbt_regression_feature_importance____id___ = MLSGBTRegressorFeatureImportance(**params)gbt_regression_feature_importance____id___.run()# @output {"label":"dataframe","name":"gbt_regression_feature_importance____id___.get_outputs()['output_port_1']","type":"DataFrame"}

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