This document discusses decision tree, a machine learning algorithm. It explains key concepts like instances, attributes, hypotheses, training and testing sets. It also provides examples of logic gates like AND, OR, XOR, NAND and NOR. References are provided to learn more about decision tree algorithms and their use in machine learning applications.

1. Decision Tree
Amir Shokri
1399/09/18

2. Decision Tree
Instances
Attribute
Hypothesis
Target Hypothesis
Sample
Training Set
Testing Set
goal of Decision Tree method
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3. Examples
AND
OR
XOR
NOR
NAND
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4. “AND”
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5. “OR”
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6. “XOR”
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7. “NAND”
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8. “NOR”
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9. References
https://www.hackerearth.com/practice/machine-learning/machine-learning-algorithms/ml-
decision-tree/tutorial/
Amir Shokri