I am just working on this project where I want to generate a multi-dimensional decision tree from a JSON dynamically. JSON has nested decision rules and each rule as node should be converted. Child nodes represent the decision points. I’ll give an example below:

{
  "rule": "A > 5",
  "true": {
   "rule": "B < 3",
  "true": {"rule": "C==1", "true": "Leaf 1", "false": "Leaf 2"},
    "false": {"rule": "D!= 4", "true": "Leaf 3", "false": "Leaf 4"}
  },
  "false": {
    "rule": "E>= 2",
    "true": {"rule": "F <6", "true": "Leaf 5", "false": "Leaf 6"},
    "false": {"rule": "G==0", "true": "Leaf 7", "false": "Leaf 8"}
  }
}

The goal is to create a decision tree using Python. Each node as instance of TreeNode class. I want the specific conditions to solve this.

class TreeNode: def __init__(self, rule, truebranch, falsebranch): self.rule = rule self.truebranch= truebranch self.falsebranch =falsebranch def evaluate(self, conditions): pass

I expect a build_tree_from_json function to perform this fucntionaliyt. I tried with some parsing of rule strings and managing different datatypes for leaf nodes in the tree.

I need guidance on:

Proper parsing operators and values.

Evaluate method should manage it all correct.

Handle egde cases precisely without errors.