mydecision_tree.py 文件源码

def RecursionTree(self, node, x, x_rows, y):
    #????
    if len(x_rows) <= 0:
      return
    #????
    if node.HasChildren() == False:
      y[x_rows] = node.GetLabel()
#      logger.debug('predict ????:%d,x_rows:%s', node.GetLabel(),x_rows)
      return

    feature = node.GetSplitAttr()
    rest_x_row = np.array(x_rows, dtype = np.int)
    for (value, child) in node.GetChildren():
      new_x_row = np.intersect1d(x_rows, np.where(x[:,feature] == value)[0])
      rest_x_row = arraysetops.setxor1d(rest_x_row, new_x_row, True)
      self.RecursionTree(child, x, new_x_row, y)

    #???????????????????????
    y[rest_x_row] = self.Classify(y, x_rows)