k均值

概述

“K-均值”节点用于产生聚类模型，用户在使用时需要指定聚类个数。K-均值算法是基于距离的算法，将所有数据归类到其最邻近的中心。

输入

输出

spark pipeline类型的模型

参数说明

样例

inputs = {
    "dataframe": None  # @input {"label":"dataframe","type":"DataFrame"}
}
params = {
    "inputs": inputs,
    "b_output_action": True,
    "b_use_default_encoder": True,  # @param {"label": "b_use_default_encoder", "type": "boolean", "required": "true", "helpTip": ""}
    "outer_pipeline_stages": None,
    "input_features_str": "",  # @param {"label": "input_features_str", "type": "string", "required": "false", "helpTip": ""}
    "cluster_feature_vector_col": "model_features",  # @param {"label": "cluster_feature_vector_col", "type": "string", "required": "true", "helpTip": ""}
    "prediction_col": "prediction",  # @param {"label": "prediction_col", "type": "string", "required": "true", "helpTip": ""}
    "k": 2,  # @param {"label": "k", "type": "integer", "required": "true", "range": "(0,2147483647]", "helpTip": ""}
    "init_mode": "random",  # @param {"label": "init_mode", "type": "string", "required": "true", "options": "random,k-means", "helpTip": ""}
    "init_steps": 2,  # @param {"label": "init_steps", "type": "integer", "required": "true", "range": "(0,2147483647]", "helpTip": ""}
    "max_iter": 20,  # @param {"label": "max_iter", "type": "integer", "required": "true", "range": "(0,2147483647]", "helpTip": ""}
    "tol": 1e-4  # @param {"label": "tol", "type": "number", "required": "true", "range": "(0.0,none)", "helpTip": ""}
}
kmeans____id___ = MLSKmeans(**params)
kmeans____id___.run()
# @output {"label":"pipeline_model","name":"kmeans____id___.get_outputs()['output_port_1']","type":"PipelineModel"}