Question 1

What is the purpose of using a neural network in data mining?

Accepted Answer

To recognize patterns in data

Answer

To encrypt data for security purposes

Answer

To create 3D visualizations of data

Answer

To delete unnecessary data from a database

Question 2

How are neural networks trained in data mining?

Accepted Answer

By adjusting the weights and biases of the network based on the error in predictions

Answer

By running the network on a quantum computer

Answer

By deleting irrelevant data from the dataset

Answer

By increasing the number of layers in the network

Question 3

What is overfitting in the context of neural networks in data mining?

Accepted Answer

When a neural network performs well on training data but poorly on unseen data

Answer

When a neural network has too few layers for complex data

Answer

When a neural network has too many activation functions

Answer

When a neural network only works well on data from a specific source

Question 4

What is an activation function in a neural network?

Accepted Answer

A function that determines the output of a neuron based on its input

Answer

A function that adds noise to the input data

Answer

A function that calculates the average of all input values

Answer

A function that changes the shape of the neural network

Question 5

What is a hidden layer in a neural network?

Accepted Answer

A layer between the input and output layers where data is processed

Answer

A layer that adjusts the weights of the network based on errors

Answer

A layer that stores the final predictions of the network

Answer

A layer responsible for receiving the initial input data

Question 6

What is the backpropagation algorithm in neural networks?

Accepted Answer

A method for adjusting the weights and biases of the network to minimize prediction errors

Answer

A technique for increasing the complexity of the neural network

Answer

A strategy for randomly initializing the weights of the network

Answer

A process for deleting unnecessary data from the dataset

Question 7

What is elitism in a genetic algorithm?

Accepted Answer

Preserving the best solutions from one generation to the next

Answer

Calculating the fitness score of each individual

Answer

Introducing random changes in offspring solutions

Answer

Selecting the most fit individuals for reproduction

Question 8

What is the selection process in a genetic algorithm?

Accepted Answer

Choosing parent solutions for crossover and mutation

Answer

Calculating the fitness score of each individual

Answer

Evaluating the fitness of offspring solutions

Answer

Introducing random changes in offspring solutions

Question 9

What is crossover in a genetic algorithm?

Accepted Answer

Combining genetic material from two parents to create new offspring

Answer

Randomly changing bits in a chromosome

Answer

Selecting the most fit individuals for reproduction

Answer

Calculating the fitness score of each individual

Question 10

What is mutation in a genetic algorithm?

Accepted Answer

Introducing random changes in offspring solutions

Answer

Selecting the most fit individuals for reproduction

Answer

Calculating the fitness score of each individual

Answer

Combining genetic material from two parents

Question 11

What is the role of fitness function in a genetic algorithm?

Accepted Answer

Evaluating how close a solution is to the optimal solution

Answer

Selecting the most fit individuals for reproduction

Answer

Introducing random changes in offspring solutions

Answer

Generating random solutions

Related quizzes

Related quizzes