What is the primary purpose of genetic algorithms in machine learning?

Genetic Algorithms in Machine Learning

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Computers, Science, Mathematics
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9th - 10th Grade
•
Hard

Patricia Brown
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10 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
To optimize learning by simulating natural selection
To create complex neural networks
To randomly guess solutions until one works
To solve problems without any predefined rules
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which of the following is NOT a step in creating a genetic algorithm?
Implementing a neural network
Creating an initial population
Defining a fitness function
Selecting the fittest members
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
In the example with Jonathan, what is a 'gene'?
A single action Jonathan can take
The obstacles Jonathan faces
The entire sequence of actions
The park Jonathan walks through
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the role of the fitness function in a genetic algorithm?
To determine the best solution by counting steps
To randomly select actions for the population
To mutate the genes of the population
To create a new generation of solutions
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How are new generations created in genetic algorithms?
By eliminating all but one solution
By manually adjusting the DNA strands
By selecting and breeding the fittest members
By randomly generating new solutions
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Why is mutation important in genetic algorithms?
To ensure the population remains diverse
To prevent the algorithm from getting stuck in local minima
To speed up the selection process
To increase the size of the population
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What happens if the mutation rate is too high?
The algorithm will converge too quickly
Jonathan will explore a lot and learn slowly
The population will become too similar
The fitness function will become ineffective
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