Example 1: how to crate a binary tree in python
class Node:
def __init__(self, data):
self.left = None
self.right = None
self.data = data
def insert(self, data):
if self.data:
if data < self.data:
if self.left is None:
self.left = Node(data)
else:
self.left.insert(data)
elif data > self.data:
if self.right is None:
self.right = Node(data)
else:
self.right.insert(data)
else:
self.data = data
def PrintTree(self):
if self.left:
self.left.PrintTree()
print( self.data),
if self.right:
self.right.PrintTree()
root = Node(12)
root.insert(6)
root.insert(14)
root.insert(3)
root.PrintTree()
Example 2: binary tree in golang
// Binary Tree in Golang
package main
import (
"fmt"
"os"
"io"
)
type BinaryNode struct {
left *BinaryNode
right *BinaryNode
data int64
}
type BinaryTree struct {
root *BinaryNode
}
func (t *BinaryTree) insert(data int64) *BinaryTree {
if t.root == nil {
t.root = &BinaryNode{data: data, left: nil, right: nil}
} else {
t.root.insert(data)
}
return t
}
func (n *BinaryNode) insert(data int64) {
if n == nil {
return
} else if data <= n.data {
if n.left == nil {
n.left = &BinaryNode{data: data, left: nil, right: nil}
} else {
n.left.insert(data)
}
} else {
if n.right == nil {
n.right = &BinaryNode{data: data, left: nil, right: nil}
} else {
n.right.insert(data)
}
}
}
func print(w io.Writer, node *BinaryNode, ns int, ch rune) {
if node == nil {
return
}
for i := 0; i < ns; i++ {
fmt.Fprint(w, " ")
}
fmt.Fprintf(w, "%c:%v\n", ch, node.data)
print(w, node.left, ns+2, 'L')
print(w, node.right, ns+2, 'R')
}
func main() {
tree := &BinaryTree{}
tree.insert(100).
insert(-20).
insert(-50).
insert(-15).
insert(-60).
insert(50).
insert(60).
insert(55).
insert(85).
insert(15).
insert(5).
insert(-10)
print(os.Stdout, tree.root, 0, 'M')
}
Example 3: binary search tree in python
Binary Search Tree at this link:
https://github.com/shreyasvedpathak/Data-Structure-Python/tree/master/BinaryTrees
Example 4: decision tree algorithm in python
clf = DecisionTreeClassifier(criterion="entropy", max_depth=3)
clf = clf.fit(X_train,y_train)
y_pred = clf.predict(X_test)
print("Accuracy:",metrics.accuracy_score(y_test, y_pred))
Example 5: binary tree in python
class Node:
def __init__(self, val):
self.l = None
self.r = None
self.v = val
class Tree:
def __init__(self):
self.root = None
def getRoot(self):
return self.root
def add(self, val):
if(self.root == None):
self.root = Node(val)
else:
self._add(val, self.root)
def _add(self, val, node):
if(val < node.v):
if(node.l != None):
self._add(val, node.l)
else:
node.l = Node(val)
else:
if(node.r != None):
self._add(val, node.r)
else:
node.r = Node(val)
def find(self, val):
if(self.root != None):
return self._find(val, self.root)
else:
return None
def _find(self, val, node):
if(val == node.v):
return node
elif(val < node.v and node.l != None):
self._find(val, node.l)
elif(val > node.v and node.r != None):
self._find(val, node.r)
def deleteTree(self):
self.root = None
def printTree(self):
if(self.root != None):
self._printTree(self.root)
def _printTree(self, node):
if(node != None):
self._printTree(node.l)
print str(node.v) + ' '
self._printTree(node.r)
tree = Tree()
tree.add(3)
tree.add(4)
tree.add(0)
tree.add(8)
tree.add(2)
tree.printTree()
print (tree.find(3)).v
print tree.find(10)
tree.deleteTree()
tree.printTree()
Example 6: binary tree in python
Binary Tree implementation at this link:
https://github.com/shreyasvedpathak/Data-Structure-Python/tree/master/BinaryTrees