source: scikit-learn.org/stable/modules/preprocessing_targets.html#preprocessing-targets 6.9. Transforming the prediction target (y) — scikit-learn 0.24.0 documentation 6.9. Transforming the prediction target (y) These are transformers that are not intended to be used on features, only on supervised learning targets. See also Transforming target in regression if you want to transform the predict..
source:scikit-learn.org/stable/modules/generated/sklearn.impute.SimpleImputer.html sklearn.impute.SimpleImputer — scikit-learn 0.24.0 documentation scikit-learn.org class sklearn.impute.SimpleImputer(*, missing_values=nan, strategy='mean', fill_value=None, verbose=0, copy=True, add_indicator=False) Imputation transformer for completing missing values. scikit-learn.org/stable/modules/impute.html#..
class sklearn.ensemble.RandomForestRegressor(n_estimators=100, *, criterion='mse', max_depth=None, min_samples_split=2, min_samples_leaf=1, min_weight_fraction_leaf=0.0, max_features='auto', max_leaf_nodes=None, min_impurity_decrease=0.0, min_impurity_split=None, bootstrap=True, oob_score=False, n_jobs=None, random_state=None, verbose=0, warm_start=False, ccp_alpha=0.0, max_samples=None) A rando..
DecisionTreeRegressor
source:scikit-learn.org/stable/modules/tree.html#tree 1.10. Decision Trees — scikit-learn 0.24.0 documentation 1.10. Decision Trees Decision Trees (DTs) are a non-parametric supervised learning method used for classification and regression. The goal is to create a model that predicts the value of a target variable by learning simple decision rules inferred from the scikit-learn.org DesicionTreeR..