Question 1

Sigmoid function is an S-shaped transfer function in the range of 0 to 1 and is also a useful ________ transfer function.

Accepted Answer

The sigmoid function is a nonlinear transfer function because it cannot be represented as a linear combination of its inputs. Its S-shaped curve allows it to map a wide range of inputs to a smaller range of outputs, making it useful in applications such as logistic regression and artificial neural networks.

Question 2

The way that information is processed by the neural network is a function of its ________.

Accepted Answer

The structure of the neural network determines how information is processed. The composition, formation, and makeup may also play a role, but they are more related to the physical aspects of the network rather than how it functions.

Question 3

________ is the most commonly used network paradigm.

Accepted Answer

Backpropagation is the most commonly used network paradigm, especially in the context of neural networks for deep learning. It is a method used for training the network by adjusting the weights in the opposite direction of the gradient of the loss function.

Question 4

Pioneers McCulloch and Pitts built their neural network model using a large number of interconnected ________ artificial neurons.

Accepted Answer

McCulloch and Pitts built their neural network model using interconnected binary (on/off) artificial neurons. The neurons could be either firing (1) or not firing (0), which allowed for a simple but powerful model of computation in which each neuron’s output (1 or 0) was determined by the weighted sum of its inputs (also 1 or 0).

Question 5

An artificial neural network is composed of many interconnected ________.

Accepted Answer

An artificial neural network is composed of many interconnected artificial neurons that process and transmit information through the network. The other choices are not accurate descriptions of the components of a neural network.

Question 6

There are about 50 to 150 billion neurons in the human brain and these neurons are partitioned into groups called ________.

Accepted Answer

Neurons in the human brain are partitioned into groups called networks.

Question 7

The ways neurons are organized are referred to as ________.

Accepted Answer

The ways neurons are organized are referred to as their topologies, which describe the spatial arrangement and connections of neuronal networks.

Question 8

Which of the following procedure is used to break datasets into different pairs of training and testing sets?

Accepted Answer

Resampling, particularly cross-validation, is commonly used to break datasets into different pairs of training and testing sets. This helps in reducing the variance in the estimates of the performance metrics of a model. Sampling, on the other hand, is commonly used to randomly select observations from a dataset. Trial and error and random are not valid options for breaking datasets into training and testing sets.

Question 9

The summation function computes the ________ sums of all the input elements entering each processing element.

Accepted Answer

The summation function computes the weighted sums of all the input elements entering each processing element, which is a fundamental operation in many digital signal processing applications and neural networks.

Question 10

The backpropagation learning algorithm is an iterative ________ technique designed to minimize an error function between the actual output of the network and its desired output,as specified in the training set of data.

Accepted Answer

The backpropagation learning algorithm uses the gradient-descent technique to adjust the weights and biases of the neural network in order to minimize the error between the actual output and the desired output. This is done through iteratively calculating the gradient of the error function with respect to each weight and bias, and updating them in the direction of steepest descent.

Question 11

In single,hidden-layer structured neural network,this hidden layer converts inputs into a ________ combination.

Accepted Answer

The correct answer is C. In a single, hidden-layer structured neural network, the hidden layer's main purpose is to convert inputs into a nonlinear combination. This nonlinear transformation allows the neural network to better capture complex relationships between the inputs and outputs, making it more efficient at solving problems such as pattern recognition and classification. Therefore, the correct choice is C, nonlinear.

Question 12

Most implementations of the learning process in neural network include a counterbalancing parameter called ________ to provide a balance to the learning rate.

Accepted Answer

The counterbalancing parameter mentioned in the question is actually called momentum. Momentum helps in providing a balance to the learning rate by allowing the network to build up speed in a particular direction, thus helping to overcome local minima or plateaus in the error surface. The momentum term allows the network to continue moving in the same direction, even when the gradient changes direction slightly, and helps the network to search more efficiently for the global minimum.

Question 13

Which of the following is not a consideration in selecting a neural network structure?

Accepted Answer

Determination of weighting functions is not a consideration in selecting a neural network structure. The other options - selection of a topology, determination of input nodes, and determination of output nodes - are important factors to consider while selecting a neural network structure.

Question 14

The connection weights express the ________ of the input data.

Accepted Answer

The answer of The connection weights express the ________ of...

Question 15

Which of the following is the reason why neural networks have been applied in business classification problems?

Accepted Answer

Neural networks have been applied in business classification problems because they are able to learn the data, learn the models' nonparametric nature, and have the ability to generalize. Neural networks are able to recognize patterns in data and learn from them, allowing them to accurately classify new data. They are also able to model complex relationships between input and output variables without making strong assumptions about the underlying distribution. Additionally, neural networks have the ability to generalize to unseen data, making them a powerful tool for business classification problems.

Question 16

Learning algorithms specify the ________ by which a neural network learns the underlying relationship between input and outputs.

Accepted Answer

Learning algorithms specify the process by which a neural network learns the underlying relationship between input and outputs.

Question 17

The output of neurons can be the final result or it can be ________ to other neurons.

Accepted Answer

The output of neurons can serve as inputs to other neurons in a neural network, allowing information to be processed and passed along. Therefore, "inputs" is the best choice.

Question 18

Which of the following is a trait of an artificial neural network?

Accepted Answer

Fault tolerance is a trait of an artificial neural network, which means the network can continue to operate even if some of its components fail or are removed. Duplicate cell and self-repaired are not traits of artificial neural networks, while memory-less is not necessarily true as some neural networks have a memory component.

Question 19

ANN can also be used as simple biological models to test ________ about biological neuronal information processing.

Accepted Answer

ANNs can be used to simulate neural processing and test hypotheses about how biological neurons process information. ANNs can be trained using a variety of inputs and outputs, and their behavior can be compared to biological neurons to gain insights into how neurons process information in the brain.

Question 20

Because of their ability to capture and represent highly complex relationships,a new and prosperous area of application for neural networks is in the field of ________.

Accepted Answer

Neural networks are particularly well-suited for applications in healthcare and medicine, where they can be used to analyze complex data and identify patterns that may not be apparent to human experts.

Quiz 6: Artificial Neural Networks for Data Mining