Visualizing the Decision Tree Process with Python
Decision tree is one of the commonly used and easy to understand machine learning algorithms. In practical applications, people often need to visualize a decision tree to better understand its decision-making process. This article will introduce how to use Python to implement the visual decision tree process.
First, we need to import some necessary libraries: numpy, pandas, graphviz and sklearn. Among them, graphviz is the key library for visualizing decision trees.
import numpy as np
import pandas as pd
from sklearn.tree import DecisionTreeClassifier
from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn