What is the process of adjusting the weights and biases of a feedforward neural network called?Select one:a.Validationb.Trainingc.Testingd.All of the above

Break Down the Problem

1. Identify the process associated with adjusting weights and biases in a feedforward neural network.
2. Analyze the provided options to determine which one correctly describes that process.

Relevant Concepts

• Validation: Refers to evaluating the model's performance on a separate dataset to ensure it can generalize well.
• Training: Involves adjusting the weights and biases of a neural network based on the input data to minimize the error.
• Testing: Similar to validation, this involves assessing the model's accuracy on a different set of unseen data.
• All of the above: Suggests that all listed processes are relevant.

Analysis and Detail

• The primary process where the weights and biases of a neural network are adjusted is during the training phase. This is done through an iterative process that includes forward propagation, loss calculation, and backward propagation (gradient descent).
• Validation and testing help assess the network's performance after training but do not involve adjusting the weights and biases.

Verify and Summarize

The main function of training is to optimize the network's performance by adjusting its parameters, unlike validation and testing, which evaluate performance.

Final Answer

The process of adjusting the weights and biases of a feedforward neural network is called b. Training.