code: def yhat_h2o_regression(m, d):
      from h2o import H2OFrame
  
      return (
          m.predict(H2OFrame(d, column_types=m._column_types))
          .as_data_frame()
          .to_numpy()
          .flatten()
      )
  
file_path: DALEX/python/dalex/dalex/_explainer/yhat.py
imports: from warnings import warn
  import numpy
label_desc: Use image node_id 8 for calling a global function with example usage: yhat_h2o_regression(m, d) and returns: m