Decision trees are useful for relatively small datasets that have a relatively simple underlying structure, and when the trained model must be easily interpretable, explains Dr. James McCaffrey of ...
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import os import cv2 import numpy as np import pandas as pd import matplotlib.pyplot as plt import time # Import the time module from sklearn.model_selection import train_test_split from ...
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