Attributes:
classes_ : array of shape = [n_classes] or a list of such arrays
The classes labels (single output problem), or a list of arrays of class labels (multi-output problem).
feature_importances_ : array of shape = [n_features]
The feature importances. The higher, the more important the feature. The importance of a feature is computed as the (normalized) total reduction of the criterion brought by that feature. It is also known as the Gini importance [R251].
max_features_ : int,
The inferred value of max_features.
n_classes_ : int or list
The number of classes (for single output problems), or a list containing the number of classes for each output (for multi-output problems).
n_features_ : int
The number of features when fit is performed.
n_outputs_ : int
The number of outputs when fit is performed.
tree_ : Tree object
The underlying Tree object.
五、决策树总结