Example code snippet for Naive Bayes fundamentals article

bayes_fruit_picker.py

import numpy as np

def choose():  # here we setup our fruit picker script
    if np.random.randint(0, 10) < 4:
        # we have chosen bag A (40% probability)
        if np.random.randint(0, 10) < 4:
            # we have chosen an apple from bag A
            return ('A', 'Apple')
        else:
            # we have chosen an orange from bag A
            return ('A', 'Orange')

    else:
        # we have chosen bag B (60% probability)
        if np.random.randint(0, 10) < 7:
            # we have chosen an apple from bag B
            return ('B', 'Apple')
        else:
            # we have chosen an orange from bag B
            return ('B', 'Orange')

# now lets count our apples
outcome = []  # initialise our list of outcomes
for _ in range(10000):
    outcome.append(  # calculate number of times we get an apple from 100 turns
           sum([1 if choose()[1] == 'Apple' else 0 for _ in range(100)]))