Build Your Own Decision Tree Using Python

Deep Insights about DT and Coding it in Python

Decision tree is one of the simplest and easiest model to run. It is one of the simplest known model for solving classification and prediction problems. It is simple to learn and visualize too. And, to be frank, in simple words, it can be easily converted into rule based system. This is the reason, I termed it as one of the easiest to understand and make others understand too. For understanding of node calculation in this model using information gain method, you can definitely look into the below post:

Decision Tree - Node Calculation

How necessary to understand Node Calculation In Decision Tree algorithm (And You Should, Too!)

Understanding for the calculation is good enough and always a gain to better understand code, lets code the same using python:

Decision Tree developed in Python

Import libraries

import pandas as pd
from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.tree…