class_docstr: Sample from the stationary version of the Friedman dataset.
  
  This sample contains 10k instances sampled from the Friedman generator.
class_docstr_tok: ["Sample","from","the","stationary","version","of","the","Friedman","dataset",".","This","sample","contains","10k","instances","sampled","from","the","Friedman","generator","."]
code: def __init__(self):
      super().__init__(
          n_samples=7000,
          n_features=10,
          task=datasets.base.REG,
          gen=datasets.synth.Friedman(seed=42),
      )
  
file_path: river/river/evaluate/gen.py
imports: from __future__ import annotations
  from river import datasets
label_desc: Use image node_id 1 to create a new Friedman7k object from inherited base classes: WrappedGenerator with example: obj = Friedman7k()