How does the RProp algorithm handle local minima in the optimization process?Select one:a.It avoids local minima by using a fixed learning rateb.It avoids local minima by using a predetermined set of learning ratesc.It gets stuck in local minimad.It avoids local minima by using a dynamic learning rate

How does the RProp algorithm adjust the learning rate?Select one:a.It uses a fixed learning rate regardless of the errorb.It increases the learning rate if the error increases and decreases the learning rate if the error decreasesc.It increases the learning rate if the error decreases and decreases the learning rate if the error increasesd.It uses a predetermined set of learning rates for each iteration

What is the main characteristic of the RProp algorithm?Select one:a.It uses a dynamic learning rateb.It uses a stochastic gradient descentc.It uses a predetermined set of weightsd.It uses a fixed learning rate

What is the RProp algorithm used for?Select one:a.Classificationb.Optimization of neural networksc.Regression analysisd.Clustering

What is the main advantage of the RProp algorithm compared to other optimization algorithms?Select one:a.It is faster and more efficientb.It is more resilient to noise and outliers in the datac.It is more accurate and precised.It is easier to implement

How does the RProp algorithm handle the initialization of weights in the optimization process?Question 12Answera.It uses the previous iteration's weightsb.It uses predetermined weightsc.It uses random weightsd.It uses the weights of the best performing iteration