What is the process of evaluating the performance of a backpropagation network called?Select one:a.Testingb.Validatingc.Inferringd.Training

Break Down the Problem

1. Identify the key terms in the question related to backpropagation networks.
2. Differentiate between the options given and their relevance to performance evaluation.

Relevant Concepts

1. Testing: This usually refers to the final evaluation of the model's performance on a separate test dataset.
2. Validating: This is the process of tuning the model's parameters during training to ensure it generalizes well to unseen data.
3. Inferring: This typically relates to making predictions using a trained model, rather than evaluating performance.
4. Training: This refers to the process where the network learns patterns from the training data using backpropagation.

Analysis and Detail

• Evaluating the performance of a backpropagation network encompasses testing and validating but primarily focuses on validation during the learning phase.
• Testing and validating involve using different datasets—the training dataset to adjust weights and biases, and the validation dataset to evaluate performance and prevent overfitting.

Verify and Summarize

• Based on the definitions: While "Testing" assesses final performance, "Validating" evaluates during the training process to optimize the model.
• The expression of evaluating performance aligns most closely with the term "Validating."

Final Answer

The correct answer is b. Validating.