WebFeb 2, 2024 · Access the max_depth for the underlying Tree object: from sklearn import tree X = [ [0, 0], [1, 1]] Y = [0, 1] clf = tree.DecisionTreeClassifier () clf = clf.fit (X, Y) print … WebFeb 19, 2024 · To find out the depth of the tree we will create an algorithm which will perform the following operations. We will recursively find out the depth of the left sub tree and right sub tree. Then get the max of both sides depth and return it.

Finding the maximum depth of a binary tree

WebFor finding the maximum depth we calculate the depth of left and right subtree. The depth of the current tree is equal to the maximum of left and right subtree +1. Thus we use a recursive approach to find the depth of left and right subtree. Since we are using recursion, we must have some base cases. WebNov 23, 2024 · You should be calling the depth method like this: return max (self.left.depth (), self.right.depth ()) + 1 The self parameter is implicitly passed to the depth method, but using it with the dot operator tells Python that this method belongs to a Node instance, and it is not some other function not bound to an object. Share Improve this answer is leather water use high or low

Geometric-based filtering of ICESat-2 ATL03 data for ground …

WebThe decision classifier has an attribute called tree_ which allows access to low level attributes such as node_count, the total number of nodes, and max_depth, the maximal depth of the tree. It also stores the entire binary tree structure, represented as a number of parallel arrays. The i-th element of each array holds information about the node i. WebGiven the root of a binary tree, return its maximum depth. A binary tree's maximum depth is the number of nodes along the longest path from the root node down to the farthest leaf … kfc gatesville contact number