Backpropagation Algorithm Optimization

Play an AI-generated podcast conversation about this lesson

What is the reason for the validation-sample error not evolving smoothly with the number of epochs?

Non-optimal learning rate

Biased validation sample

Noise in the data

Local minima in the error surface (correct)

What is the benefit of selecting a slower stopping rate in the presence of local minima?

Increased robustness to noise

Improved generalization performance (correct)

Faster convergence

Reduced overfitting

What is the primary function of feature extraction in convolution networks?

To optimize the learning rate

To reduce overfitting

To extract local features (correct)

To perform dimensionality reduction

What is the primary advantage of convolution networks?

High degree of invariance to translation, scaling, and skewing Signup and view all the answers

What is the primary limitation of the early-stopping method?

It is sensitive to the choice of stopping criteria Signup and view all the answers

What is the primary benefit of using cross-validation in the early-stopping method?

Improved generalization performance Signup and view all the answers

What happens to the local gradient when weights are assigned small initial values?

It becomes very small and causes learning to slow down. Signup and view all the answers

Why is the origin a saddle point on the error surface?

Because the curvature is positive across the error surface and negative along it. Signup and view all the answers

What is the advantage of setting the standard deviation of the induced field between the linear and saturated parts of the sigmoid?

It allows the neuron to operate in the linear region of the sigmoid. Signup and view all the answers

What is the assumption made about the inputs applied to the MLP?

They have zero mean and unit variance. Signup and view all the answers

Why should weights not be too large or too small?

Because it can cause the neuron to operate in the saturated region of the sigmoid. Signup and view all the answers

What is the purpose of initializing the synaptic weights from a uniformly distributed set of numbers with zero mean?

To ensure the neuron operates in the linear region of the sigmoid. Signup and view all the answers

What is the primary goal of early-stopping method of training?

To achieve good generalization by preventing overfitting Signup and view all the answers

What happens to the MSE as the number of epochs increases?

It decreases Signup and view all the answers

What is done periodically during the early-stopping method of training?

The validation error is measured Signup and view all the answers

What can be inferred from the shape of the validation curve?

The model is overfitting Signup and view all the answers

How often is the estimation (training) interrupted during the early-stopping method of training?

Every five epochs Signup and view all the answers

What is the purpose of the validation subset in the early-stopping method of training?

To test the model's generalization capabilities Signup and view all the answers