class_docstr: ContinuousIntervalTree tree node.
code: def predict_proba(self, X, n_classes):
      if self.best_split > -1:
          if X[self.best_split] <= self.best_threshold:
              return self.children[0].predict_proba(X, n_classes)
          elif X[self.best_split] > self.best_threshold:
              return self.children[1].predict_proba(X, n_classes)
          else:
              return self.children[2].predict_proba(X, n_classes)
      else:
          return self.leaf_distribution
  
imports: import sys
  import numpy
  from sklearn import preprocessing
  from sklearn.base import BaseEstimator
  from sklearn.utils import check_random_state
  from sktime.exceptions import NotFittedError
label_desc: Use image node_id 3 for calling the _TreeNode obj's underlying member method code with example usage: obj.predict_proba(X, n_classes) and returns: self, self, self, self