text: -- @testpoint: kmeans创建mode,带不正确的超参verbose,合理报错
  
  --step1: 建表并插入数据;expect: 建表并插入数据成功
  drop table if exists t_model_tab_0124;
  create table t_model_tab_0124(id integer not null,
      "position" double precision[] not null,
      closest_centroid integer not null,
      l1_distance double precision not null,
      l2_distance double precision not null,
      l2_squared_distance double precision not null,
      linf_distance double precision not null );
  insert into t_model_tab_0124 values (214,'{82.2331969052000034,-52.153098620199998,-64.0339866000999933,-.325498639699999981,-64.6012442075999947,-81.5499670644999952,59.6012426708999989}',3,10.0679804578999992,4.35061571650000012,18.9278571126999999,2.38415523010000019);
  
  --step2: kmeans创建mode,带不正确的超参verbose;expect: 创建失败,报错提参数verbose值错误
  create model m_model_max_iterations_0124 using kmeans from (select position from t_model_tab_0124) with verbose = 4,num_features = 7;
  
  --step3: 清理环境;expect: 清理成功
  drop table t_model_tab_0124;