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Code: Alles auswählen

def objective(trial):
      n_estimators = trial.suggest_int("n_estimators",20, 1000)
      max_depth = trial.suggest_int("max_depth",5,500)
   
      rf = RandomForestClassifier(n_estimators=n_estimators, max_depth=max_depth, min_impurity_decrease=min_impurity_decrease, min_samples_split =min_samples_split, min_samples_leaf=min_samples_leaf,
                                  bootstrap=False, max_features="auto")
      scores = cross_val_score(rf, X_train, y_train, scoring = "accuracy", cv = 10)
      return scores.mean()
      
study = optuna.create_study(direction = "maximize")
study.optimize(objective, n_trials=10000)

Code: Alles auswählen

  # Confusion Matirx
  predictions= cross_val_predict(model,X_main, y_main, cv = 10)

  # Report für recall/precision/accuracy/f1
  report = classification_report(y_main,predictions)