Decision Tree algorithm in Scikit-Learn
Decision Tree Algorithm Example
A Decision Tree algorithm formulates a tree composed of root nodes (points where a choice must be made), branch nodes (binary yes/no answers to the choice) and leaf nodes (represent variables).
In this example, numpy and matplotlib are used to plot a decision tree structure represented by parallel arrays with different properties:
import numpy as np
from matplotlib import pyplot as plt
from sklearn.model_selection import train_test_split
from sklearn.datasets import load_iris
from sklearn.tree import DecisionTreeClassifier
from sklearn import tree
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