RandomForestRegressor(bootstrap=True, ccp_alpha=0.0, criterion='mse', max_depth=None, max_features='auto', max_leaf_nodes=None, max_samples=None, min_impurity_decrease=0.0, min_impurity_split=None, min_samples_leaf=1, min_samples_split=2, min_weight_fraction_leaf=0.0, n_estimators=100,...
Trains a random forest algorithm with 70% of data. Spark’s RandomForestRegressor is used to train a model for regression problems. The RandomForestClassifier is used to train a model for classification problems. Evaluates a random forest model with the remaining 30% of data. Data Wrangler eval...
Among the eight referenced studies, the random forest method has been implemented most frequently, with a testing R2value greater than 0.75 (as shown in Fig.1). To establish a set of general diagrams for different thermal conversion processes, we consistently employ the random forest regressor for...