class_docstr: Benchmarks for RandomForestClassifier.
class_docstr_tok: ["Benchmarks","for","RandomForestClassifier","."]
code: def make_estimator(self, params):
      representation, n_jobs = params
  
      n_estimators = 500 if Benchmark.data_size == "large" else 100
  
      estimator = RandomForestClassifier(
          n_estimators=n_estimators,
          min_samples_split=10,
          max_features="log2",
          n_jobs=n_jobs,
          random_state=0,
      )
  
      return estimator
  
imports: from sklearn.ensemble import GradientBoostingClassifier, HistGradientBoostingClassifier, RandomForestClassifier
  from .common import Benchmark, Estimator, Predictor
  from .datasets import _20newsgroups_highdim_dataset, _20newsgroups_lowdim_dataset, _synth_classification_dataset
  from .utils import make_gen_classif_scorers
label_desc: Use image node_id 3 for calling the RandomForestClassifierBenchmark obj's underlying member method code with example usage: obj.make_estimator(params) and returns: estimator