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Created 2 years ago
ABISHEK A S - 18MIS1077
The decision trees are calculated using the concept of entropy and information gain.
import pandas as pd
import numpy as np
eps = np.finfo(float).eps
from numpy import log2 as log
Creating a dataset, which represents the Eating condition based on the Taste, Temperature, Texture
dataset = {
'Taste': [
'Salty', 'Spicy', 'Spicy', 'Spicy', 'Spicy', 'Sweet', 'Salty', 'Sweet',
'Spicy', 'Salty'
],
'Temperature':
['Hot', 'Hot', 'Hot', 'Cold', 'Hot', 'Cold', 'Cold', 'Hot', 'Cold', 'Hot'],
'Texture': [
'Soft', 'Soft', 'Hard', 'Hard', 'Hard', 'Soft', 'Soft', 'Soft', 'Soft',
'Hard'
],
'Eat': ['No', 'No', 'Yes', 'No', 'Yes', 'Yes', 'No', 'Yes', 'Yes', 'Yes']
}