Genetic algorithm mutation rate about ml-from-scratch HOT 7 CLOSED

Given that the mutation rate parameter is compared against a value sampled randomly between 0 and 1 mutation will be applied in proportion to the mutation rate value provided. E.g. for mutation rate set to 0.6, mutation will be applied ~60% of the times given that the random value is uniformly sampled between 0 and 1.

from ml-from-scratch.

Run this experimental code.

import numpy
mutation_rate = 0.6
times = 0
for i in range(10):
if numpy.random.random() < mutation_rate:
times += 0.1
print(times)

The random value is uniformly sampled but it isn't applied 60% of the time. It is also random.

from ml-from-scratch.

It's applied 100% of the time but it's true roughly 60% of the time. See below.

Eriks-MacBook-Pro:~ erik$ python3
Python 3.7.0 (default, Jun 29 2018, 20:13:13) 
[Clang 9.1.0 (clang-902.0.39.2)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import numpy as np
>>> val = 0
>>> for _ in range(100000):
...     if np.random.random() < 0.6:
...             val += 1
... 
>>> print (val)
59966

from ml-from-scratch.

Run it multiple times and compare the results. Numpy's random value generation is independent of boolean comparisons.

from ml-from-scratch.

Mutation rate is commonly implemented as a probability of mutation with respect to the mutation rate parameter. Because of this it's implemented as a comparison between a random value and the parameter.

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You don't understand what I was trying to communicate, anyways, you did a good job.

from ml-from-scratch.

This is handled similarly to what I've seen in several other reference implementations of GA. Check https://blog.sicara.com/getting-started-genetic-algorithms-python-tutorial-81ffa1dd72f9 in the section where mutation is implemented for instance. The argument that setting a higher mutation rate would not have an impact is clearly false as the statement np.random.random() < mutation_rate would be true more often and mutation would thereby be applied more often.

from ml-from-scratch.