Neural Networks MCQs – T4Tutorials.com

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1. : What is the primary application of neural networks in data mining?
(A) Clustering
(B) Regression
(C) Classification and Regression
(D) Association rule mining

2. : What is a “neuron” in the context of neural networks?
(A) A cluster of data points
(B) A processing unit that receives inputs, processes them, and produces an output
(C) A decision node in a decision tree
(D) A type of kernel function

3. : What is the activation function in a neural network used for?
(A) To initialize the weights
(B) To introduce non-linearity into the model
(C) To reduce the dimensionality of the data
(D) To normalize the inputs

4. : Which of the following is NOT a commonly used activation function in neural networks?
(A) Sigmoid
(B) ReLU (Rectified Linear Unit)
(C) Tanh
(D) Euclidean distance

5. : What is the purpose of the backpropagation algorithm in training neural networks?
(A) To randomly initialize the weights
(B) To update the weights to minimize the loss function
(C) To transform the data into a higher-dimensional space
(D) To split the data into training and test sets

6. : In the context of neural networks, what does “overfitting” refer to?
(A) When the model is too simple to capture the underlying patterns
(B) When the model performs well on training data but poorly on test data
(C) When the model has too few layers
(D) When the model converges too quickly

7. : What is a “hidden layer” in a neural network?
(A) The input layer
(B) The output layer
(C) Any layer between the input and output layers
(D) A layer that does not affect the output

8. : What is the role of the learning rate in the training of a neural network?
(A) To determine the number of neurons in each layer
(B) To control the size of the steps taken during weight updates
(C) To decide the number of hidden layers
(D) To split the data into batches

9. : What does the term “epoch” refer to in the context of training neural networks?
(A) A single update of the weights
(B) One forward and backward pass of all the training examples
(C) A subset of the training data
(D) The number of layers in the neural network

10. : Which of the following techniques is commonly used to prevent overfitting in neural networks?
(A) Increasing the learning rate
(B) Using a more complex model
(C) Applying regularization techniques like dropout
(D) Reducing the number of training examples

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By: Prof. Dr. Fazal Rehman | Last updated: May 14, 2025

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