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2. [Marks: 40%] Using the UCI wine dataset (https://archive.ics.uci.edu/ml/datasets/Wine), generate a binary decision tree of maximum depth = 4. No need to split into
2. [Marks: 40%] Using the UCI wine dataset (https://archive.ics.uci.edu/ml/datasets/Wine), generate a binary decision tree of maximum depth = 4. No need to split into training/testing. Submit: [1] your code in a file named wine.py, and [2] the tree in a file named wine.jpeg. You may want to install GraphViz to generate the jpeg image of the tree.
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1 import pandas as pd import numpy as np from sklearntree import DecisionTreeClassifier from sklearntree import exportgraphviz from IPythondisplay imp...
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Mobile Communications
Authors: Jochen Schiller
2nd edition
978-0321123817, 321123816, 978-8131724262
