random_forest.py 文件源码

def __init__(self, n_estimators=100, max_features=None, min_samples_split=2,
                 min_gain=0, max_depth=float("inf")):
        self.n_estimators = n_estimators    # Number of trees
        self.max_features = max_features    # Maxmimum number of features per tree
        self.min_samples_split = min_samples_split
        self.min_gain = min_gain            # Minimum information gain req. to continue
        self.max_depth = max_depth          # Maximum depth for tree
        self.progressbar = progressbar.ProgressBar(widgets=bar_widgets)

        # Initialize decision trees
        self.trees = []
        for _ in range(n_estimators):
            self.trees.append(
                ClassificationTree(
                    min_samples_split=self.min_samples_split,
                    min_impurity=min_gain,
                    max_depth=self.max_depth))