Neural network training is accomplished by repeatedly passing the training data through the network while
A) individual network weights are modified.
B) training instance attribute values are modified.
C) the ordering of the training instances is modified.
D) individual network nodes have the coefficients on their corresponding functional parameters modified.

Question

Quizplus · Accepted Answer

Neural network training involves modifying the weights of the network based on the training data. This is typically achieved through an optimization process such as gradient descent, which adjusts the weights based on the error between the network's output and the desired output for each training instance. Option B and C do not accurately describe the training process, and D is not a commonly used term in neural network training.

Neural Network Training Is Accomplished by Repeatedly Passing the Training